An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
Plato Stanford. A computational philosophy account on Abduction, one of the three thinking patterns besides Induction and Deduction, being unique for its potential to introduce new ideas into current knowledge.
Plato Stanford. A computational philosophy account on Scientific Explanation, a canonical application of Abduction.
Plato Stanford. A computational philosophy account on Scientific Reduction, which comes with no explicit boundary with Explanation.
Plato Stanford. A computational philosophy account on Non-monotonic Logic, a family of formal frameworks devised to capture and represent defeasible inference.
Courier Corporation, 1955. [All Versions]. Original writings by C. S. Peirce, the philosopher who first introduces the concept of Abduction.
Routledge, 1991. [All Versions]. Lipton's original paper on Inference to the Best Explanation as a specialized condition of Abduction.
Springer, 2000. [All Versions]. This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches.
Springer, 2009. [All Versions]. Most philosophers of science in the twentieth century have concluded that no logic of creative processes exists and, moreover, that a rational model of discovery is impossible. In short, scientific creative inferences are irrational and there is no “reasoning” to…
The Oxford Handbook of Thinking and Reasoning, 2012. [All Versions]. This chapter reviews evidence from cognitive psychology and cognitive development concerning the structure and function of explanations, with a focus on the role of explanations in learning and inference. The findings highlight…
Trends in Cognitive Sciences, 2006. [All Versions]. Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational systems such as graphs…
Trends in Cognitive Sciences, 2006. [All Versions]. Generating and evaluating explanations is spontaneous, ubiquitous and fundamental to our sense of understanding. Recent evidence suggests that in the course of an individual's reasoning, engaging in explanation can have profound effects on the…
Trends in Cognitive Sciences, 2016. [All Versions]. People often learn by seeking explanations, and they assess the viability of hypotheses by considering how well they explain the data. An emerging body of work reveals that both children and adults have strong and systematic intuitions about what…
Cognition, 2015. [All Versions]. This paper investigates experimentally controversy in philosophy about the connection between explanation and inference, of whether judgments of the explanatory goodness of hypotheses do play a role when people revise their degrees of belief in those hypotheses…
Journal of Cognitive Psychology, 2016. [All Versions]. There is evidence that people update their credences partly on the basis of explanatory considerations. Philosophers have recently argued that to minimise the inaccuracy of their credences, people's updates also ought to be partly based on…
Journal of Experimental Psychology, 2018. [All Versions]. There is a wealth of evidence that people’s reasoning is influenced by explanatory considerations. Three experiments investigate the descriptive adequacy of a precise proposal to be found in the philosophical literature, to wit, that we…
Trends in Cognitive Sciences, 2021. [All Versions]. Philosophers have argued that people ought to change their graded beliefs via Bayes’ rule. Recent work in psychology indicates that people sometimes violate that rule by attending to explanatory factors. Results from computational modeling…
Cognitive Science, 2001. [All Versions].
Proceedings of the National Academy of Sciences, 2013. [All Versions]. This paper presents a theory, and its computer implementation, of how mental simulations underlie the abductions of informal algorithms and deductions from these algorithms. Three experiments tested the theory’s predictions,…
Synthese, 2007. [All Versions]. A categorization for Abduction in the account of pure philosophy.
Journal of Applied Logic, 2015. [All Versions].
Philosophy of Science, 1999. [All Versions].
Synthese, 2011. [All Versions].
Synthese, 2019. [All Versions].
Spatial Cognition, 2002. [All Versions].
Synthese, 2018. [All Versions].
New Generation Computing, 2019. [All Versions].
Frontiers in Psychology, 2015. [All Versions]. A non-Bayesian account of Abduction.
ICAART, 2021. [All Versions]. A probabilistic perspective for interpreting Abductive Reasoning.
Journal of Experimental & Theoretical Artificial Intelligence, 2006. [All Versions].
Model-Based Reasoning in Science and Technology, 2010. [All Versions]. The distinctions and relations between Abduction, Induction, and Analogy.
Cognition, 2018. [All Versions]. A rational account of human hypothesis generation.
Cognitive Science, 2012. [All Versions].
Current Opinion in Behavioral Sciences, 2020. [All Versions]. A piece of developmental pshchological evidence for Abduction in young children.
2022. [All Versions]. This work presents a grammar for expressing hypotheses in visual data analysis to formalize the previously abstract notion of "analysis tasks." Through the lens of this grammar, the authors lay the groundwork for how a user's data analysis questions can be operationalized and…
Plato Stanford. A computational philosophy account on Scientific Discovery, the process or product of successful scientific inquiry, sometimes an Abduction-like (Explanation) thinking pattern.
Springer, 1977. [All Versions]. The original book on search as scientific thinking.
MIT Press, 1987. [All Versions]. The book is divided into four parts. Part I introduces the subject of discovery, defines the scope of our work, and discusses some of the issues that have surrounded and still surround our topic. Parts II and III contain the main body of our results, largely in the…
MIT Press, 2000. [All Versions]. In this book, D. Klahr sets out to describe the cognitive and developmental processes that have enabled scientists to make the discoveries that comprise the body of information we call "scientific knowledge." Over the past decade, Klahr and his colleagues have…
Cognitive Science, 1988. [All Versions]. The original paper on the dual space search as scientific thinking theory.
CogSci'92, 1992. [All Versions]. Previous psychological research about scientific discovery has often focused on subjects' heuristics for discovering simple concepts with one relevant dimension or a few relevant dimensions with simple two-way interactions. This paper presents results from an…
International Journal of Human-Computer Studies, 1996. [All Versions]. This paper describes a cognitive model of exploratory learning, which covers both trial-and-error and instruction-taking activities. The model, implemented in Soar, is grounded in empirical data of subjects in a task-oriented,…
Cognitive Psychology, 1993. [All Versions]. A piece of evidence on children have basic scientific thinking skills.
CogSci'95, 1995. [All Versions]. Extending the dual space search.
Memory & Cognition, 1996. [All Versions]. When evaluating experimental evidence, how do people deal with the possibility that some of the feedback is erroneous? The potential for error means that evidence evaluation must include decisions about when to “trust the data.” This paper presents two…
Psychological Review, 1987. [All Versions]. A psychological account on hypothesis testing.
Psychological Review, 2011. [All Versions].
Psychological Review, 1989. [All Versions]. A perspective against search as scientific thinking.
Synthese, 2021. [All Versions]. A computational philosophy account connecting Abduction and scientific thinking.
Cognitive Development, 2015. [All Versions]. A variety of theories have been put forth to explain the function of imagination, most notably that imagination engages and develops children's theory of mind and counterfactual reasoning. This work proposes that a primary role for imagination is as a…
Trends in Cognitive Sciences, 2019. [All Versions]. Humans often represent and reason about unrealized possible actions---the vast infinity of things that were not (or have not yet been) chosen. This capacity is central to the most impressive of human abilities: causal reasoning, planning,…
Behavioral and Brain Sciences, 2020. [All Versions]. [Preprint]. Rationalization occurs when a person has performed an action and then concocts the beliefs and desires that would have made it rational. Then, people often adjust their own beliefs and desires to match the concocted ones. While many…
Trends in Cognitive Sciences, 2021. [All Versions]. Humans are remarkably limited in: (i) how many control-dependent tasks they can execute simultaneously, and (ii) how intensely they can focus on a single task. These limitations are universal assumptions of most theories of cognition. Yet, a…
Behavioral and Brain Sciences, 2021. [All Versions]. Imaginary worlds are extremely successful. The most popular fictions produced in the last few decades contain such a fictional world. They can be found in all fictional media, from novels (e.g., Lord of The Rings and Harry Potter) to films…
CogSci'16, 2016. [All Versions]. Models of concept learning and theory acquisition often invoke a stochastic search process, in which learners generate hypotheses through some structured random process and thenevaluate them on some data measuring their quality or value. To be successful within a…
Nature, 2004. [All Versions]. This paper describes a physically implemented robotic system that applies techniques from artificial intelligence to carry out cycles of scientific experimentation. The system automatically originates hypotheses to explain observations, devises experiments to test…
Artificial Intelligence, 1993. [All Versions]. Abduction is inference to the best explanation. The authors have developed an approach to abductive inference, called “weighted abduction”, that has resulted in a significant simplification of how the problem of interpreting texts is conceptualized.…
Artificial Intelligence, 1993. [All Versions]. This paper presents a simple framework for Horn-clause abduction, with probabilities associated with hypotheses. The framework incorporates assumptions about the rule base and independence assumptions amongst hypotheses. It is shown how any…
Advances in Bayesian Networks, 2004. [All Versions]. The goal of this paper is to serve as a survey for the problem of abductive inference (or belief revision) in Bayesian networks. Thus, the problem is introduced in its two variants: total abduction (or MPE) and partial abduction (or MAP) . Also,…
Journal of Logic Computation, 1992. [All Versions]. This paper is a survey and critical overview of recent work on the extension of logic programming to perform abductive reasoning (abductive logic programming). The authors outline the general framework of abduction and its applications to…
The Journal of Logic Programming, 1999. [All Versions]. This paper presents the framework of Abductive Constraint Logic Programming (ACLP), which integrates Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP). In ACLP, the task of abduction is supported and enhanced by its…
Computational Logic, 2002. [All Versions]. [Preprint]. Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to…
IJCAI'11, 2011. [All Versions]. [Preprint]. This work introduces Bayesian Abductive Logic Programs (BALP), a probabilistic logic that adapts Bayesian Logic Programs (BLPs) for abductive reasoning. Like BLPs, BALPs also combine first-order logic and Bayes nets. However, unlike BLPs, which use…
ECML'11, 2011. [All Versions]. Plan recognition is the task of predicting an agent’s top-level plans based on its observed actions. It is an abductive reasoning task that involves inferring cause from effect. Most existing approaches to plan recognition use either first-order logic or…
IJCAI'13, 2013. [All Versions]. Abduction has been extensively studied in propositional logic because of its many applications in artificial intelligence. However, its intrinsic complexity has been a limitation to the implementation of abductive reasoning tools in more expressive logics. The…
AAAI'19, 2019. [All Versions]. The growing range of applications of Machine Learning (ML) in a multitude of settings motivates the ability of computing small explanations for predictions made. Small explanations are generally accepted as easier for human decision makers to understand. Most earlier…
IJCAI'21, 2021. [All Versions]. Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been proposed. This paper introduces probabilistic sufficient explanations, which formulate…
COLING, 1990. [All Versions]. Many existing approaches to machine translation take for granted that the information presented in the output is found somewhere in the input, and, moreover, that such information should be expressed at a single representational level, say, in terms of the parse trees…
AAAI Spring Symposium Series 2021 on Artificial Intelligence for Synthetic Biology, 2021. [All Versions]. This work proposes an automated biodesign engineering framework empowered by Abductive Meta-Interpretive Learning (MetaAbd), a novel machine learning approach that combines symbolic and…
AAAI Spring Symposium Series 2023 on Computational Scientific Discovery, 2023. [All Versions]. [Extended Abstract]. [Slides]. This work introduces a novel machine learning framework ILP-iML1515 based on Inductive Logic Programming (ILP) that performs abductive logical reasoning and actively learns…
Nature Machine Intelligence, 2022. [All Versions]. Randomized controlled trials (RCTs) are considered the gold standard for testing causal hypotheses in the clinical domain; however, the investigation of prognostic variables of patient outcome in a hypothesized cause–effect route is not feasible…
Plato Stanford. A computational philosophy account on the nature of uncertainty modeling in Bayesian Epistemology.
Nature, 2015. [All Versions]. Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic…
Behavioral and Brain Sciences, 2001. [All Versions]. [Preprint]. Shepard has argued that a universal law should govern generalization across different domains of perception and cognition, as well as across organisms from different species or even different planets. Starting with some basic…
NeurIPS'98, 1998. [All Versions]. [Preprint]. This work considers the problem of learning concepts from small numbers of positive examples, a feat which humans perform routinely but which computers are rarely capable of. Bridging machine learning and cognitive science perspectives, this work…
NeurIPS'99, 1999. [All Versions]. [Preprint]. This paper argues that two apparently distinct modes of generalizing concepts - abstracting rules and computing similarity to exemplars - should both be seen as special cases of a more general Bayesian learning framework. Bayes explains the specific…
Trends in Cognitive Sciences, 2006. [All Versions]. [Preprint]. Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction…
Psychological Review, 2007. [All Versions]. [Preprint]. The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents,…
Science, 2011. [All Versions]. [Preprint]. This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of…
Science, 2015. [All Versions]. [Preprint]. [Supplementary Material]. People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar accuracy. People can also use…
Behavioral and Brain Sciences, 2017. [All Versions]. [Preprint]. Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition,…
Nature Human Behavior, 2024. [All Versions]. [Preprint]. This perspective shows how the science of collaborative cognition can be put to work to engineer systems that really can be called ‘thought partners’, systems built to meet humans' expectations and complement humans' limitations. The authors…
CogSci'01, 2001. [All Versions].
NeurIPS'11, 2011. [All Versions].
CogSci'12, 2012. [All Versions].
CogSci'21, 2021. [All Versions]. Rule- and similarity-based generalization in colexification.
Science Advances, 2024. [All Versions]. This paper introduces a computational model designed to emulate human inductive reasoning on abstract reasoning tasks, such as those in IQ tests, using a minimax entropy approach. This method combines identifying the most effective constraints on data via…
Statistical Machine Learning Tutorials, 2022. This tutorial on generative modeling is in part of Statistical Machine Learning Tutorial by Ying Nian Wu at UCLA Statistics. The tutorial goes over the key equations and algorithms for learning recent generative models, including energy-based models,…
Chapman and Hall/CRC, 1995. [All Versions]. Don Rubin's introductory book on Bayesian models.
International Journal of Computer Vision, 1998. [All Versions]. [Preprint]. This article presents a statistical theory for texture modeling. This theory combines filtering theory and Markov random field modeling through the maximum entropy principle, and interprets and clarifies many previous…
Annual Review of Psychology, 2004. [All Versions]. [Preprint]. We perceive the shapes and material properties of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Typical images are highly complex because they consist of many objects embedded in…
Quarterly of Applied Mathematics, 2018. [All Versions]. [Preprint]. The pattern theory of Grenander is a mathematical framework where patterns are represented by probability models on random variables of algebraic structures. In this paper, the authors review three families of probability models,…
Quarterly of Applied Mathematics, 2008. [All Versions]. [Preprint]. One fundamental property of natural image data that distinguishes vision from other sensory tasks such as speech recognition is that scale plays a profound role in image formation and interpretation. Specifically, visual objects…
ICML'16, 2016. [All Versions]. The authors show that a generative random field model, which they call generative ConvNet, can be derived from the commonly used discriminative ConvNet, by assuming a ConvNet for multi-category classification and assuming one of the category is a base category…
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. [All Versions]. This paper studies the cooperative training of two generative models for image modeling and synthesis. Both models are parametrized by convolutional neural networks (ConvNets). The first model is a deep…
NeurIPS'20, 2020. [All Versions]. [Project]. [Code]. A milestone paper on Latent Energy-Based Model.
ICLR'21, 2021. [All Versions]. [Code].
ICLR'21, 2021. [All Versions].
ICML'20, 2020. [All Versions].
Neural Computing, 1997. [All Versions]. [Preprint]. This article proposes a general theory and methodology, called the minimax entropy principle, for building statistical models for images (or signals) in a variety of applications. This principle consists of two parts. The first is the maximum…
Journal of the American Statistical Association, 1999. [All Versions]. [Preprint]. Viewing the observed data of a statistical model as incomplete and augmenting its missing parts are useful for clarifying concepts and central to the invention of two well-known statistical algorithms:…
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002. [All Versions]. [Preprint]. This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contributes to image…
NeurIPS'06, 2006. [All Versions].
Predicting Structured Data, MIT Press, 2006. [All Versiosn]. Yann LeCun's tutorial on energy-based learning.
ICLR'16, 2016. [All Versions].
Journal of Machine Learning Research, 2019. [All Versions]. This paper provides new insights on the Unadjusted Langevin Algorithm. The authors show that this method can be formulated as the first order optimization algorithm for an objective functional defined on the Wasserstein space of order…
Science, 2017. [All Versions]. [Preprint]. Learning from a few examples and generalizing to markedly different situations are capabilities of human visual intelligence that are yet to be matched by leading machine learning models. By drawing inspiration from systems neuroscience, this work…
Cognitive Psychology, 2017. [All Versions]. [Preprint]. Why are human inferences sometimes remarkably close to the Bayesian ideal and other times systematically biased? In particular, why do humans make near-rational inferences in some natural domains where the candidate hypotheses are explicitly…
The Annals of Statistics, 1973. [All Versions]. [Preprint]. A classic review on non-parametric problems.
The Annals of Statistics, 1974. [All Versions]. The original paper on Dirichlet Process modeling for non-parametric problems.
Journal of Computer and System Sciences, 2000. [All Versions]. The original paper on hierarchical topic model.
Statistical Science, 2004. [All Versions]. This paper reviews the current state of nonparametric Bayesian inference. The discussion follows a list of important statistical inference problems, including density estimation, regression, survival analysis, hierarchical models and model validation. For…
Proceedings of the National Academy of Sciences, 2004. [All Versions]. A first step in identifying the content of a document is determining which topics that document addresses. This paper describes a generative model for documents, in which each document is generated by choosing a distribution…
NeurIPS'03, 2003. [All Versions]. The original paper for nested Chinese restaurant process.
AAAI'06, 2006. [All Versions].
Journal of the ACM, 2010. [All Versions].
Gatsby Computational Neuroscience Unit Technical Report 2005-001, 2005. [All Versions].
Journal of Machine Learning Research, 2011. [All Versions]. The Indian buffet process is a stochastic process defining a probability distribution over equivalence classes of sparse binary matrices with a finite number of rows and an unbounded number of columns. This distribution is suitable for…
UAI'05, 2005. [All Versions]. [Preprint]. The Bayesian Logic (BLOG) language was recently developed for defining first-order probability models over worlds with unknown numbers of objects. It handles important problems in AI, including data association and population estimation. This paper extends…
UAI'06, 2006. [All Versions]. [Preprint]. Relational learning analyzes the probabilistic constraints between the attributes of entities and relationships. This work extends the expressiveness of relational models by introducing for each entity (or object) an infinite-dimensional latent variable as…
ICML'07, 2007. [All Versions]. This work proposes statistical predicate invention as a key problem for statistical relational learning. SPI is the problem of discovering new concepts, properties and relations in structured data, and generalizes hidden variable discovery in statistical models and…
Proceedings of the IEEE, 2015. [All Versions]. [Preprint]. Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems, and large-scale heterogeneous computing and storage architectures. The construction of such systems involves…
NeurIPS'12, 2012. [All Versions]. The use of machine learning algorithms frequently involves careful tuning of learning parameters and model hyperparameters. Unfortunately, this tuning is often a “black art” requiring expert experience, rules of thumb, or sometimes brute-force search. There is…
2018. [All Versions]. Bayesian optimization is an approach to optimizing objective functions that take a long time (minutes or hours) to evaluate. It is best-suited for optimization over continuous domains of less than 20 dimensions, and tolerates stochastic noise in function evaluations. It…
Matter. [All Versions]. Autonomous experimentation achieves user objectives more efficiently than Edisonian studies by combining machine learning and laboratory automation to iteratively select and perform experiments. Integrating knowledge from theory, simulations, literature, and human intuition…
Plato Stanford. A collection of the computational philosophical debates about the concepts.
Wikipedia. Wikipedia for the Theory theory, a perspective that contextualizes concepts in theoretical (or empirical) systems.
MIT Press, 1985. [All Versions]. Susan Carey's book on the theory theory of concepts in child development.
MIT Press, 1997. [All Versions]. Alison Gopnik's book that articulates and defends the "theory theory" of cognitive and semantic development, the idea that infants and young children, like scientists, learn about the world by forming and revising theories-a view of the origins of knowledge and…
Mapping the mind: Domain specificity in cognition and culture, Cambridge University Press, 1994. [All Versions]. Alison Gopnik's original paper on the theory theory.
Oxford University Press, 2009. [All Versions]. Susan Carey's extended book on the theory theory of concepts in child development.
2023. [All Versions]. The aim of this multidisciplinary workgroup was to establish consensus definitions for some of the major recurring constructs in semantic research (e.g., concept, amodal, abstract). These efforts yielded a glossary consisting of succinct definitions, agreement, subjective…
Psychological Bulletin, 2012. [All Versions]. Alison Gopnik's review on the constructivism idea of developmental research, including the theory theory of concepts.
Psychological Science, 1990. [All Versions]. Theory on similarity judgement by attributes and relations.
Science, 2016. [All Versions]. [Preprint]. It has been hypothesized that the brain organizes concepts into a mental map, allowing conceptual relationships to be navigated in a manner similar to that of space. Grid cells use a hexagonally symmetric code to organize spatial representations and are…
Science, 2018. [All Versions]. [Preprint]. The hippocampal formation has long been suggested to underlie both memory formation and spatial navigation. This work discusses how neural mechanisms identified in spatial navigation research operate across information domains to support a wide spectrum…
Trends in Cognitive Sciences, 2021. [All Versions]. [Preprint]. Humans and animals use mental representations of the spatial structure of the world to navigate. The classical view is that these representations take the form of Euclidean cognitive maps, but alternative theories suggest that they…
Nature, 2016. [All Versions]. [Preprint]. [Code & Tutorial]. The meaning of language is represented in regions of the cerebral cortex collectively known as the ‘semantic system’. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is…
Psychological Science, 2021. [All Versions]. [All Versions]. Humans primarily rely on language to communicate, on the basis of a shared understanding of the basic building blocks of communication: words. Do we mean the same things when we use the same words? Although cognitive neural research on…
Nature Human Behavior, 2022. [All Versions]. [Preprint]. How is knowledge about word meaning represented in the mental lexicon? Current computational models infer word meanings from lexical co-occurrence patterns. They learn to represent words as vectors in a multidimensional space, wherein words…
Frontiers in Psychology, 2014. [All Versions]. The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what…
Cerebral Cortex, 2023. [All Versions]. [Preprints]. Shape processing, whether by seeing or touching, is pivotal to object recognition and manipulation. Although the low-level signals are initially processed by different modality-specific neural circuits, multimodal responses to object shapes have…
Scientific Data, 2020. [All Versions]. [Project]. Advances in computer-assisted linguistic research have been greatly influential in reshaping linguistic research. With the increasing availability of interconnected datasets created and curated by researchers, more and more interwoven questions can…
Cognition, 2023. [All Versions]. An evidence-based study concluding that people call category members to mind according to their location in representational space, specifically based on the predicted usefulness of considering category members with particular features.
Trends in Cognitive Sciences, 2024. [All Versions]. For decades, cognitive scientists have debated what kind of representation might characterize human concepts. Whatever the format of the representation, it must allow for the computation of varied properties, including similarities, features,…
Science, 2023. [All Versions]. [Code]. [Data (Reproduced)]. [Preprint]. [GoodScents Database]. [Leffingwell Database]. Mapping molecular structure to odor perception is a key challenge in olfaction. This work used graph neural networks to generate a principal odor map (POM) that preserves…
eLife, 2023. [All Versions]. [Code & Data]. Odorous compounds with similar POM representations are more likely to co-occur within a substance and be metabolically closely related; metabolic reaction sequences also follow smooth paths in POM despite large jumps in molecular structure.
IEEE Transactions on Robotics, 2020. [All Versions]. [Preprint]. Tactile sensing is a key sensor modality for robots interacting with their surroundings. These sensors provide a rich and diverse set of data signals that contain detailed information collected from contacts between the robot and its…
CVPR'23, 2023. [All Versions]. [Project]. This work presents ImageBind, an approach to learn a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. The authors show that all combinations of paired data are not necessary to train such a joint…
CogSci'22, 2022. [All Versions]. Semantic features have been playing a central role in investigating the nature of our conceptual representations. Yet the enormous time and effort required to empirically sample and norm features from human raters has restricted their use to a limited set of…
CVPR'19, 2019. [All Versions]. [Project]. Humans perceive the world using multi-modal sensory inputs such as vision, audition, and touch. This work investigates the cross-modal connection between vision and touch. The main challenge in this cross-domain modeling task lies in the significant scale…
Transactions of the Association for Computational Linguistics, 2022. [All Versions]. Testing the concept representation by neural networks through Fodor's theory of concepts.
ACL'24, 2024. [All Versions]. A preliminary work empirically showing that the intermediate embeddings of multilingual Transformers (1) start far away from output token embeddings; (2) already allow for decoding a semantically correct next token in the middle layers, but give higher probability to…
Trends in Cognitive Sciences, 2024. [All Versions]. [Preprint]. In what sense does a large language model (LLM) have knowledge? The authors answer by granting LLMs ‘instrumental knowledge’: knowledge gained by using next-word generation as an instrument. The authors then ask how instrumental…
The Bell System Technical Journal, 1948. [All Versions]. Shannon's original paper on Information Theory.
Springer, 2008. [All Versions]. The introductory book for Algorithmic Information Theory, especially the Kolmogorov complexity theory.
Psychological Review, 1972. [All Versions]. Herbert Simon's review on subjective complexity.
IRE Transactions on Information Theory, 1962. [All Versions].
IBM Journal of Research and Development, 1977. [All Versions]. Chaitin's original paper on Algorithmic Information Theory.
NeurIPS'03, 2003. [All Versions].
ICML'23, 2023. [All Versions]. [Project]. [Models]. This work examines concept generalization at a large scale in the natural visual spectrum. Established computational modes (i.e., rule-based or similarity-based) are primarily studied isolated, focusing on confined and abstract problem spaces.…
Nature Machine Intelligence, 2025. [All Versions]. The rapid development of artificial intelligence (AI) systems has created an urgent need for their scientific quantification. While their fluency across a variety of domains is impressive, AI systems fall short on tests requiring algorithmic…
Science, 2000. [All Versions]. The original paper on spectrum clustering.
Science, 2006. [All Versions]. The original paper on Variational Autoencoder.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013. [All Versions]. Yoshua Bengio's review on representation learning.
Annual Review of Statistics and Its Application, 2020. [All Versions]. Song-Chun Zhu and Ying Nian Wu's review on representation learning, in an account of statistics.
IEEE Information Theory Workshop'15, 2015. [All Versions]. The first paper identifying the problem of information bottleneck in representation learning.
Journal of Statistical Mechanics: Theory and Experiment, 2019. [All Versions].
Psychological Bulletin, 2006. [All Versions]. [APA]. A psychological account on visual complexity.
Displays, 2005. [All Versions]. Compressed file size, an objective, easily obtained measure of display complexity, predicts both subjective complexity judgments and objective search performance. It is analogous to algorithmic complexity, a theoretical but impractical measure of bit string…
International Workshop on Quality of Multimedia Experience, 2013. [All Versions].
Journal of Experimental Psychology, 2022. [All Versions]. [APA]. Empirical evidencs showing the relation between visual complexity and description length.
Trends in Cognitive Sciences, 2022. [All Versions]. A comprehensive review on the trade-off between variability and generalization ability.
CogSci'22, 2022. [All Versions].
Cognition, 2023. [All Versions]. The findings of this paper suggest that language communicates complex concepts by directly transmitting abstract rules. In contrast, demonstrations transmit examples, requiring the learner to infer the rules.
Cognitive Science, 2010. [All Versions]. Nicolas Fay's original paper on iconicity.
Pragmatics & Cognition, 2014. [All Versions]. This paper explores the role of iconicity in spoken language and other human communication systems.
Behavior Modification, 1994. [All Versions].
Cognitive Science, 2007. [All Versions]. The first paper introducing the graphical language game.
Journal of Pragmatics, 2014. [All Versions].
ACM SIGGRAPH'20, 2020. [All Versions]. [Project]. Rationality in feature sketching.
Computational Brain & Behavior, 2020. [All Versions]. A computational account on the rational behavior in graphical language games.
NeurIPS, 2022. [All Versions]. A computational account on the emergence of iconic language.
ACM SIGGRAPH Asia'23, 2023. [All Versions]. By continually observing their environment and communicating, AI agents trained in the Chinese dictionary and the Nüshu corpus collaborate towards creating a standard writing system to encode Chinese.
Proceedings of the National Academy of Sciences, 2021. [All Versions]. Simulating the emergence of code as the communication bottleneck in color learning task.
CogSci'22, 2022. [All Versions].
Cognition, 2008. [All Versions]. The original paper on child pointing.
Journal of Cognition and Development, 2009. [All Versions].
Knowledge and Information Systems, 2006. [All Versions].
Plato Stanford. A computational philosophy account of Pragmatics, whilch studies utterances in specific contexts.
Science, 2012. [All Versions]. [Preprint]. One of the most astonishing features of human language is its capacity to convey information efficiently in context. Many theories provide informal accounts of communicative inference, yet there have been few successes in making precise, quantitative…
Trends in Cognitive Sciences, 2016. [All Versions]. Understanding language requires more than the use of fixed conventions and more than decoding combinatorial structure. Instead, comprehenders make exquisitely sensitive inferences about what utterances mean given their knowledge of the speaker,…
Semantics & Pragmatics, 2016. [All Versions].
Semantics and Linguistic Theory, 2016. [All Versions]. Adjective understanding as a rational inference in the context.
Transactions of the Association for Computational Linguistics, 2017. [All Versions].
Child Development, 2019. [All Versions]. A piece of evidence for children's capability on social pragmatics.
NAACL'18, 2018. [All Versions].
EMNLP Findings'20, 2020. [All Versions]. Application of Rational Speech Act to Image Captioning.
CogSci'19, 2019. [All Versions].
Nature Human Behavior, 2021. [All Versions]. Before formal education begins, children typically acquire a vocabulary of thousands of words. This learning process requires the use of many different information sources in their social environment, including their current state of knowledge and the…
Semantics and Pragmatics, 1998. [All Versions].
Philosophical Studies, 2021. [All Versions].
ICML'23 Workshop on Theory-of-Mind, 2023. [All Versions]. [Project].
Humanities and Social Sciences Communications, 2020. [All Versions]. [Code & Data]. [Dialogue Experimental Toolkit(DiET)]. The present study sets out to experimentally investigate how environmental factors come to shape the emergence of linguistic conventions. To this end, the authors adapt the…
Urban Experience and Design: Contemporary Perspectives on Improving the Public Realm, 2020. [All Versions]. [OSMnx Tool]. [OpenStreetMap Website].
Cognition, 1987. [All Versions].
Cognition, 1994. [All Versions].
Plato Stanford. A computational philosophy account on compositionality, one of the distinctive feature of language.
Nature, 2024. [All Versions]. This perspective brings recent evidence from neuroscience and allied disciplines to argue that in modern humans, language is a tool for communication, contrary to a prominent view that we use language for thinking. The authors begins by introducing the brain network…
Topoi, 1994. [All Versions]. The original paper on the principle of semantic compositionality.
Proceedings of the Evolution of Language Conference'06, 2006. [All Versions]. The original paper on the emergence of compositionality.
ICLR'17, 2017. [All Versions]. The original paper on the emergence of language in multi-agent reinforcement learning.
NeurIPS'18, 2018. [All Versions].
ICLR'18, 2018. [All Versions].
Psychological Review, 2019. [All Versions].
ACL'20, 2020. [All Versions].
CogSci'22, 2022. [All Versions].
2023. [All Versions].
Science Robotics, 2022. [All Versions]. [Preprint]. This paper proposes an explainable artificial intelligence (XAI) system in which a group of robots predicts users’ values by taking in situ feedback into consideration while communicating their decision processes to users through explanations. To…
AAMAS'24, 2024. [All Versions]. Drawing inspiration from human team cooperative learning, this paper proposes a novel paradigm that facilitates a gradual shift from explicit communication to tacit cooperation.
Nature Machine Intelligence, 2025. [All Versions]. Human feedback on conversations with language models is central to how these systems learn about the world, improve their capabilities and are steered towards desirable and safe behaviours. However, this feedback is mostly collected by frontier…
AAMAS'26, 2026. [All Versions]. Benchmarks are crucial for assessing multi-agent reinforcement learning (MARL) algorithms. While StarCraft II-related environments have driven significant advances in MARL, existing benchmarks like SMAC focus primarily on micromanagement, limiting comprehensive…
Wikipedia. Wikipedia encyclopedia entry on Domain Specific Languages.
Wikipedia. Wikipedia encyclopedia entry on Domain Engineering.
Pearson Education, 2010. [All Versions]. [Domain-Specific Languages Guide]. When carefully selected and used, Domain-Specific Languages (DSLs) may simplify complex code, promote effective communication with customers, improve productivity, and unclog development bottlenecks. In Domain-Specific…
Wikipedia. Programming languages may support multiple programming paradigms. This Wikipedia encyclopedia entry lists a concise reference for the programming paradigms.
ACM SIGPLAN Notices, 1982. [All Versions].
. An introduction to Domain Specific Languages (DSL) based on 19 DSL cases.
ACM Computing Surveys, 2005. [All Versions]. [Preprint]. Domain-specific languages (DSLs) are languages tailored to a specific application domain. They offer substantial gains in expressiveness and ease of use compared with general-purpose programming languages in their domain of application. DSL…
OOPSLA Workshop on Domain-Specific Modeling (DSM' 09), 2009. [All Versions]. Designing a new domain specific language is as any other complex task sometimes error-prone and usually time consuming, especially if the language shall be of high-quality and comfortably usable. Existing tool support…
ACM SIGPLAN Notices, 2000. [All Versions]. A survey on the topic of domain-specific languages as used for the construction and maintenance of software systems. The survey lists a selection of 75 key publications in the area, and provides a summary for each of the papers. Moreover, the survey…
ICQICT'12, 2012. [All Versions]. [Preprint]. The purpose of this proposal is to contribute to the systematic activity of Software Language Engineering by focusing on the issue of the Usability evaluation of DSLs. Usability evaluation is often skipped, relaxed, or at least omitted from papers…
Domain Engineering: Product Lines, Languages, and Conceptual Models, 2013. [All Versions]. In recent years, the development of domain-specific modeling languages has gained remarkable attention. This is for good reasons. A domain-specific modeling language incorporates concepts that represent…
Information and Software Technology, 2016. [All Versions]. This study reports on a Systematic Mapping Study (SMS) for Domain-Specific Languages (DSLs). The main objective of the described work was to perform an SMS on DSLs to better understand the DSL research field, identify research trends, and…
ACM Transactions on Software Engineering and Methodology, 2024. [All Versions]. Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents to software engineering researchers the six key challenges that a domain expert faces in…
ACM Transactions on Computer-Human Interaction, 2021. [All Versions]. Programming language design requires making many usability-related design decisions. However, existing HCI methods can be impractical to apply to programming languages: languages have high iteration costs, programmers require…
Journal of Systems and Software, 2015. [All Versions]. A DSL aims to support software development by offering abstractions to a particular domain. It is expected that DSLs improve the maintainability of artifacts otherwise produced with general-purpose languages. However, the maintainability of…
ACM Computing Surveys, 2015. [All Versions]. Domain-Specific Aspect Languages (DSALs) are Domain-Specific Languages (DSLs) designed to express crosscutting concerns. Compared to DSLs, their aspectual nature greatly amplifies the language design space. This survey structures this space in order to…
IEEE Transactions on Visualization and Computer Graphics, 2022. [All Versions]. There has been substantial growth in the use of JSON-based grammars, as well as other standard data serialization languages, to create visualizations. Each of these grammars serves a purpose: some focus on particular…
OOPSLA'23, 2023. [All Versions]. Programming tools are increasingly integral to research and analysis in myriad domains, including specialized areas with no formal relation to computer science. Embedded domain-specific languages (eDSLs) have the potential to serve these programmers while placing…
ICIRA'24, 2024. [All Versions]. [Preprint]. Crafting automation systems tailored for specific domains requires aligning the space of human experts’ semantics with the space of robot executable actions, and scheduling the required resources and system layout accordingly. Regrettably, there are…
VIS-Gen4DS'24, 2024. [All Versions]. [Preprint]. A position paper on DSL for data-driven storytelling. Data-driven storytelling serves as a crucial bridge for communicating ideas in a persuasive way. However, the manual creation of data stories is a multifaceted, labor-intensive, and case-specific…
Nature Synthesis, 2024. [All Versions]. While abstraction is critical for the transferability of automated laboratory science in (bio)chemical and materials sciences, its improper implementation is a technical debt taken against the reproducibility of experimental results. Over the decades,…
ACL'24, 2024. [All Versions]. [Preprint]. [Project]. The original paper on the automated design of DSLs, referred to as AutoDSL. Accurate representation of procedures in restricted scenarios, such as non-standardized scientific experiments, requires precise depiction of constraints. Unfortunately,…
ICLR'25, 2025. [All Versions]. [Project]. Self-driving laboratories have begun to replace human experimenters in performing single experimental skills or predetermined experimental protocols. However, as the pace of idea iteration in scientific research has been intensified by Artificial…
Science, 2019. [All Versions]. [Preprint]. [Perspective: Democratizing synthesis by automation]. This paper develops an autonomous compiler and robotic laboratory platform to synthesize organic compounds on the basis of standardized methods descriptions. The platform comprises conventional…
Nature Chemistry, 2020. [All Versions]. [Preprint]. Although the automatic synthesis of molecules has been established, each reaction class uses bespoke hardware. This means that the connection of multi-step syntheses in a single machine to run many different protocols and reactions is not…
Journal of Biological Engineering, 2010. [All Versions]. [Project]. [Microsoft Page] This paper introduces BioCoder, a C++ library that enables biologists to express the exact steps needed to execute a protocol. In addition to being suitable for automation, BioCoder converts the code into a…
Nature Synthesis, 2024. [All Versions]. [Preprint]. The amount of chemical synthesis literature is growing quickly; however, it takes a long time to share and evaluate new processes among laboratories. This paper presents an approach that uses a universal chemical programming language (χDL) to…
Nature Communications, 2024. [All Versions]. Robotic platforms for chemistry are developing rapidly but most systems are not currently able to adapt to changing circumstances in real-time. This paper presents a dynamically programmable system capable of making, optimizing, and discovering new…
ACM Journal on Emerging Technologies in Computing Systems, 2023. [All Versions]. Laboratory protocols are critical to biological research and development, yet difficult to communicate and reproduce across projects, investigators, and organizations. While many attempts have been made to address…
UIST'23, 2023. [All Versions]. [Project]. This paper presents KnitScript, a domain-specific machine knitting scripting language that supports computationally driven knitting designs. KnitScript provides a comprehensive virtual model of knitting machines, giving access to machine-level capabilities…
Precision Agriculture, 2020. [All Versions]. This paper proposes a domain-specific language framework for the design and development of precision-agriculture FMISs, which copes with challenges on supporting the understandability, enhancing communication and analysis of the design decisions, and…
2021. [All Versions]. [Corel recipe page]. [International Network of Food Data Systems (INFOODS)]. The Corel DSL for cooking recipes enables understanding of and computation with ingredients, and can construct a nutrition label for the recipe.
CVPR'23, 2023. [All Versions]. [Website]. [Supplementary Text]. This paper introduces Infinigen, a procedural generator of photorealistic 3D scenes of the natural world. Infinigen is entirely procedural: every asset, from shape to texture, is generated from scratch via randomized mathematical…
CVPR'24, 2024. [All Versions]. This work introduces Infinigen Indoors, a Blender-based procedural generator of photorealistic indoor scenes. It builds upon the existing Infinigen system, which focuses on natural scenes, but expands its coverage to indoor scenes by introducing a diverse library of…
CHI EA'24, 2024. [All Versions]. [Preprint]. Large language models can produce creative and diverse responses. However, to integrate them into current developer workflows, it is essential to constrain their outputs to follow specific formats or standards. This work surveyed 51 experienced industry…
Science, 2024. [All Versions]. Many clinically used drugs are derived from natural microbial products that are assembled in a stepwise fashion by the condensation of amino acids or acyl groups. Using insights from evolutionary analysis, two independent groups now show that the cumbersome enzyme…
Nature Communications, 2024. [All Versions]. The material acceleration platform, empowered by robotics and artificial intelligence, is a transformative approach for expediting material discovery processes across diverse domains. However, the development of an operating system for material…
Nature Biotechnology, 2010. [All Versions]. [Preprint]. Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. BioPAX can represent metabolic and signaling pathways, molecular…
Science, 2021. [All Versions]. The ability for viruses to mutate and evade the human immune system and cause infection, called viral escape, remains an obstacle to antiviral and vaccine development. Understanding the complex rules that govern escape could inform therapeutic design. This work…
2022. [All Versions]. Combining a basic set of building blocks into more complex forms is a universal design principle. Most protein designs have proceeded from a manual bottom-up approach using parts created by nature, but top-down design of proteins is fundamentally hard due to biological…
Nature Communications, 2023. [All Versions]. [Project]. Advances in machine learning (ML) and automated experimentation are poised to vastly accelerate research in polymer science. Data representation is a critical aspect for enabling ML integration in research workflows, yet many data models…
OpenLaw.io. It is now possible to model all or parts of legal agreements using code (smart contracts), decreasing the cost and friction of creating, securing, and generating binding legal agreements. Lawyers lack basic tools to build these dynamic, “smart” contracts in a way that is enforceable…
Machine Learning, 2022. [All Versions]. This paper proposes a domain-specific language, Scenic, for describing scenarios that are distributions over scenes and the behaviors of their agents over time. Scenic combines concise, readable syntax for spatiotemporal relationships with the ability to…
ICBC'20, 2020. [All Versions]. [Preprint]. This research addresses the understanding hardness raised from the conceptual discrepancy between contractual clauses and corresponding code of the Solidity programming language, by the design and study of a domain-specific smart contract language based…
Information and Software Technology, 2022. [All Versions]. Smart contracts play a vital role in many fields. Despite being called smart, the development of smart contracts is a tedious task beyond defining a set of contractual rules. In addition to business knowledge, coding a smart contract…
ICML'21, 2021. [All Versions]. This work presents PClean, a probabilistic programming language (PPL) for leveraging dataset-specific knowledge to automate Bayesian cleaning, automating Bayesian approaches given the diversity of real-world error patterns and the hardness of inference.
ICML'21, 2021. [All Versions]. [Project]. This paper presents Omega, a probabilistic programming language with support for counterfactual inference. This feature is accomplished by introducing a new operator to probabilistic programming akin to Pearl’s do.
ISPLC'11, 2011. [All Versions]. [Preprint]. This paper investigates the application of domain-specific languages in product line engineering (PLE). It starts by analyzing the limits of expressivity of feature models. Feature models correspond to context-free grammars without recursion, which…
ETFA'21, 2021. [All Versions]. This paper presents the design of the PPR-DSL to effectively and efficiently represent Product-Process-Resource (PPR) aspects and evaluate constraints defined for modeling PPR views in the Formalized Process Description standard (VDI 3682).
International Journal of Computer Vision, 2018. [All Versions]. [Preprint]. This work proposes a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground truth information,…
CVPR'25, 2025. [All Versions]. [Project]. This paper introduces the Scene Language, a visual scene representation that concisely and precisely describes the structure, semantics, and identity of visual scenes. It represents a scene with three key components: a program that specifies the…
Science, 2021. [All Versions]. Pathological changes in alternative splicing patterns are considered a hallmark of cancer, yet the underlying regulatory programs that control this process remain largely unknown. A major obstacle to better understanding these programs is that the bioinformatic…
Nature Human Behavior, 2025. [All Versions]. [Project]. People are remarkably capable of generating their own goals, beginning with child’s play and continuing into adulthood. Despite considerable empirical and computational work on goals and goal-oriented behaviour, models are still far from…
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020. [All Versions]. Detection, parsing, and future predictions on sequence data (e.g., videos) require the algorithms to capture non-Markovian and compositional properties of high-level semantics. Context-free grammars are natural…
International Journal of Computer Vision, 2025. [All Versions]. This position paper argues for the use of structured generative models (SGMs) for the understanding of static scenes. This requires the reconstruction of a 3D scene from an input image (or a set of multi-view images), whereby the…
Nature, 2023. [All Versions]. Messenger RNA (mRNA) vaccines are being used to combat the spread of COVID-19, but they still exhibit critical limitations caused by mRNA instability and degradation, which are major obstacles for the storage, distribution and efficacy of the vaccine products.…
ACM Transactions on Graphics, 2020. [All Versions]. This work introduces a system called Penrose for creating mathematical diagrams. Its basic functionality is to translate abstract statements written in familiar math-like notation into one or more possible visual representations. Rather than rely…
EEWC'19, 2019. [All Versions]. Nowadays legal ontologies have been used in the legal domain, however, being poorly explored in legislative and production processes. This paper analyses the adoption of legal ontologies as a tool to support these processes, in particular, related to activities span…
ACM Transactions on Graphics, 2023. [All Versions]. Garment modeling is an essential task of the global apparel industry and a core part of digital human modeling. Realistic representation of garments with valid sewing patterns is key to their accurate digital simulation and eventual fabrication.…
IEEE Transactions on Visualization and Computer Graphics, 2024. [All Versions]. Visualizations play a critical role in validating and improving statistical models. However, the design space of model check visualizations is not well understood, making it difficult for authors to explore and specify…
ACM Transactions on Graphics, 2020. [All Versions]. This work presents RoboGrammar, a fully automated approach for generating optimized robot structures to traverse given terrains. This framework represents each robot design as a graph, and uses a graph grammar to express possible arrangements of…
Wikipedia. Wikipedia on Situation Calculus, a logic formalism designed for representing and reasoning about dynamical domains.
Springer, 2008. [All Versions]. [Tutorial on AAAI]. Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems. As an outgrowth of research on the use of nonmonotonic reasoning in knowledge representation, it is particularly useful in…
ICLPNR'99, 1999. [All Versions]. [Preprint]. The original paper on Answer Set Programming (ASP), a form of declarative programming oriented towards difficult search problems, on the use of nonmonotonic reasoning in knowledge representation. In ASP solutions to a problem are represented by answer…
The Logic Programming Paradigms, 1999. [All Versions]. [Preprint]. This is a discussion of some of the achievements and challenges related to representing actions and the design of planners from the perspective of logic programming. The authors talk about recent work on action languages and…
Artificial Intelligence, 1986. [All Versions]. [Preprint]. This paper presents a precise definition of qualitative structure and behavior descriptions as abstractions of differential equations and continuously differentiable functions. The authors present a new algorithm for qualitative simulation…
MIT Press, 1994. [All Versions]. This book presents, within a conceptually unified theoretical framework, a body of methods that have been developed over the past fifteen years for building and simulating qualitative models of physical systems - bathtubs, tea kettles, automobiles, the physiology…
Artificial Intelligence, 1997. [All Versions]. Shortcomings of qualitative simulation and of quantitative simulation motivate combining them to do simulations exhibiting strengths of both. The resulting class of techniques is called semiquantitative simulation. One approach to semi-quantitative…
ACS Synthetic Biology, 2018. [All Versions]. This paper presents a logic programming language that allows a broad range of computational nucleic acid systems to be designed and analyzed. The language extends standard logic programming with a novel equational theory to express nucleic acid…
Nature Protocol, 2022. [All Versions]. [Preprint]. Cells interact with their environment, communicate among themselves, track time and make decisions through functions controlled by natural regulatory genetic circuits consisting of interacting biological components. Synthetic programmable circuits…
ACM Transactions on Graphics, 2025. [All Versions]. While large vision-language models can generate motion graphics animations from text prompts, they regularly fail to include all of spatio-temporal properties described in the prompt. This work introduces MoVer, a motion verification DSL based on…
ICLR'25, 2025. [All Versions]. Compression is at the heart of intelligence. A theoretically optimal way to compress any sequence of data is to find the shortest program that outputs that sequence and then halts. However, such Kolmogorov compression is uncomputable, and code generating LLMs…
Scientific Reports, 2022. [All Versions]. Inferring reliable brain-behavior associations requires synthesizing evidence from thousands of functional neuroimaging studies through meta-analysis. However, existing meta-analysis tools are limited to investigating simple neuroscience concepts and…
Scientific Data, 2024. [All Versions]. Although cellular senescence is a key factor in organismal aging, with both positive and negative effects on individuals, its mechanisms remain largely unknown. Thus, integrating knowledge is essential to explain how cellular senescence manifests in tissue…
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. [All Versions]. This paper proposes a novel Knowledge-based Embodied Question Answering (K-EQA) task, in which the agent intelligently explores the environment to answer various questions with the knowledge. Different from…
IEEE Transactions on Robotics, 2022. [All Versions]. Successful plan generation for autonomous systems is necessary but not sufficient to guarantee reaching a goal state by an execution of a plan. Various discrepancies between an expected state and the observed state may occur during the plan…
IEEE Transactions on Computers, 2024. [All Versions]. With the growth of smart systems and applications, high volume logs are generated that record important data for system maintenance. System developers are usually required to analyze logs to track the status of the system or applications.…
NeurIPS'18, 2018. [All Versions]. The method learns a model that uses program synthesis techniques to recover a graphics program from drawing primitives. These programs have constructs like variable bindings, iterative loops, or simple kinds of conditionals. With a graphics program in hand, we can…
POPL'23, 2023. [All Versions]. This paper proposes library learning modulo theory (LLMT), a new library learning algorithm that additionally takes as input an equational theory for a given problem domain. LLMT uses e-graphs and equality saturation to compactly represent the space of programs…
POPL'23, 2023. [All Versions]. This paper introduces corpus-guided top-down synthesis as a mechanism for synthesizing library functions that capture common functionality from a corpus of programs in a domain specific language (DSL). The algorithm builds abstractions directly from initial DSL…
Philosophical Transactions of the Royal Society A, 2023. [All Versions]. [Preprint]. This paper presents DreamCoder, a system that learns to solve problems by writing programs. It builds expertise by creating domain-specific programming languages for expressing domain concepts, together with…
Nature Communications, 2022. [All Versions]. Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. This work presents a framework for algorithmically synthesizing models of a basic part of human language:…
NeurIPS'23, 2023. [All Versions]. Grammar prompting is a simple approach to enable LLMs to use external knowledge and domain-specific constraints expressed through a grammar in Backus--Naur Form (BNF) during in-context learning. Grammar prompting augments each demonstration example with a…
2023. [All Versions]. [Project]. [Website]. This paper proposes CLAIRIFY, an approach that combines automatic iterative prompting with program verification to ensure programs written in data-scarce domain-specific language are syntactically valid and incorporate environment constraints.
ACM SIGCHI'24, 2024. [All Versions]. This paper explores a new multi-modal image search approach that allows users to conveniently specify and perform semantic image search tasks. With the tool, PhotoScout, the user interactively provides natural language descriptions, positive and negative…
NeurIPS'24, 2024. [All Versions]. [Project]. Recent development in Artificial Intelligence (AI) models has propelled their application in scientific discovery, but the validation and exploration of these discoveries require subsequent empirical experimentation. The concept of self-driving…
Nature, 2024. [All Versions]. Large language models (LLMs) have demonstrated tremendous capabilities in solving complex tasks, from quantitative reasoning to understanding natural language. However, LLMs sometimes suffer from confabulations (or hallucinations), which can result in them making…
UIST'24, 2024. [All Versions]. This paper adopted an iterative design process to gain insights into programmers’ strategies when using LLMs for programming. The authors proposed CoLadder, a novel system that supports programmers by facilitating hierarchical task decomposition, direct code segment…
ACM Transactions on Graphics, 2018. [All Versions]. While computer-aided design is a major part of many modern manufacturing pipelines, the design files typically generated describe raw geometry. Lost in this representation is the procedure by which these designs were generated. This paper…
ACM SIGCHI Symposium on Engineering Interactive Computing Systems, 2018. [All Versions]. [Code]. [Website]. This paper shows that deep learning methods can be leveraged to train a model end-to-end to automatically reverse engineer user interfaces and generate code from a single input image with…
ACM Transactions on Graphics, 2022. [All Versions]. CAD modeling, despite being the industry-standard, remains restricted to usage by skilled practitioners due to two key barriers. First, the user must be able to mentally parse a final shape into a valid sequence of supported CAD commands; and…
ACM Transactions on Graphics, 2020. [All Versions]. Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling alternatives. Procedural representations are one such possibility: they offer high-quality and editable results but are difficult to…
ACM Transactions on Graphics, 2021. [All Versions]. A popular way to create detailed yet easily controllable 3D shapes is via procedural modeling, i.e. generating geometry using programs. Such programs consist of a series of instructions along with their associated parameter values. To fully…
ACM Transactions on Graphics, 2023. [All Versions]. This work introduces ShapeCoder, the first system capable of taking a dataset of shapes, represented with unstructured primitives, and jointly discovering (i) useful abstraction functions and (ii) programs that use these abstractions to explain…
International Journal of Robotics Research, 2020. [All Versions]. Movement primitives are a well studied and widely applied concept in modern robotics. However, composing primitives out of an existing library has shown to be a challenging problem. This work proposes the use of probabilistic…
IEEE Transactions on Automation Science and Engineering, 2024. [All Versions]. This paper presents LogiCode, a novel framework that leverages Large Language Models (LLMs) for identifying logical anomalies in industrial settings, moving beyond the traditional focus on structural inconsistencies. By…
ACM Transactions on Database Systems, 2020. [All Versions]. This article targets the Incremental View Maintenance (IVM) of sophisticated analytics (such as statistical models, machine learning programs, and graph algorithms) expressed as linear algebra programs. This work presents LAGO, a unified…
NeurIPS'23, 2023. [All Versions]. Program synthesis aims to automatically generate an executable program that conforms to the given specification. Recent advancements have demonstrated that deep neural methodologies and large-scale pretrained language models are highly proficient in capturing…
ACM Transactions on Software Engineering and Methodology, 2025. [All Versions]. Large language models (LLMs) such as ChatGPT have shown remarkable capabilities in code generation. Despite significant achievements, they rely on enormous training data to acquire a broad spectrum of open-domain…
Trends in Cognitive Sciences, 2020. [All Versions]. The scope of human learning and development poses a radical challenge for cognitive science. The authors propose that developmental theories can address this challenge by adopting perspectives from computer science. Many of our best models treat…
Nature Human Behavior, 2025. [All Versions]. Individuals rely on others’ expertise to achieve a basic understanding of the world. But how can non-experts achieve understanding from explanations that, by definition, they are ill-equipped to assess? Across 9 experiments with 6,698 participants…
NeurIPS'22, 2022. [All Versions]. While humans readily generate and interpret instructions in a general language, computer systems are shackled to a narrow domain-specific language that they can precisely execute. This makes building intelligent systems that can generalize to novel situations such…
Nature Communications, 2024. [All Versions]. Symbolic models based on program learning successfully explain rule-learning in many domains, but performance degrades quickly as program complexity increases. It remains unclear how to scale symbolic rule-learning methods to model human performance in…
Psychological Review, 1958. [All Versions]. Herbert Simon's original idea on human problem solving.
Englewood Cliffs, NJ: Prentice-hall, 1972. [All Versions]. Herbert Simon's classic idea of human problem solving as search.
Taylorfrancis, 2010. [All Versions].
Science, 1974. [All Versions]. Daniel Kahneman's classic idea of prospective theory.
Proceedings of the National Academy of Sciences, 2020. [All Versions]. A piece of evidence on hierarchical human planning.
Science, 2019. [All Versions]. Neuroscience evidence supporting rule switch.
Nature, 2013. [All Versions]. The original paper introducing mixed selectivity with high-dimensional neural representations.
Nature, 2022. [All Versions]. A computational account on rational problem representation in human planning.
Trends in Cognitive Sciences, 2023. [All Versions]. A review that outlines the computational and biological principles that enable the brain to compute the usefulness of an option or action by creating abstractions that flexibly adapt to changing goals.
eLife, 2022. [All Versions].
Machine Learning, 1991. [All Versions].
Cognitive Science, 1994. [All Versions].
Cognitive Science, 1997. [All Versions].
Proceedings of the National Academy of Sciences, 2020. [All Versions]. [Project]. [Appendix]. Many animals, and an increasing number of artificial agents, display sophisticated capabilities to perceive and manipulate objects. But human beings remain distinctive in their capacity for flexible,…
CogSci'20, 2020. [All Versions].
NeurIPS'21, 2021. [All Versions].
Current Opinion in Behavioral Sciences, 2020. [All Versions].
Current Opinion in Behavioral Sciences, 2021. [All Versions].
Cell, 2021. [All Versions].
Proceedings of the National Academy of Sciences, 2009. [All Versions]. [Supplementary Material]. A piece of evidence on creative tool use in intelligent animals.
CogSci'18, 2018. [All Versions]. [Code].
Nature Human Behavior, 2017. [All Versions].
Science Robotics, 2019. [All Versions]. Humans can infer concepts from image pairs and apply those in the physical world in a completely different setting, enabling tasks like IKEA assembly from diagrams. If robots could represent and infer high-level concepts, then it would notably improve their…
Journal of Artificial Intelligence Research, 2018. [All Versions]. This work considers the problem of constructing abstract representations for planning in high-dimensional, continuous environments. The authors assume an agent equipped with a collection of high-level actions, and construct…
Annual Review of Control, Robotics, and Autonomous Systems, 2021. [All Versions]. The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task…
Robotics: Science and Systems, 2018. [All Versions].
CogSci'21, 2018. [All Versions].
Cognitive Science, 2021. [All Versions].
AAAI'22, 2022. [All Versions].
NeurIPS'04, 2004. [All Versions]. A comprehensive review on intrinsic reward functions in classic reinforcement learning.
Frontiers in Neurorobotics, 2009. [All Versions].
Journal of Artificial Intelligence Research, 2020. [All Versions].
ICML'17, 2017. [All Versions]. The original paper on curiosity as intrinsic motivation.
2017. [All Versions].
ICML'21, 2021. [All Versions].
NeurIPS'15, 2015. [All Versions]. The original paper on empowerment as intrinsic motivation.
2022. [All Versions].
Nature Human Behavior, 2021. [All Versions].
IEEE Transactions on Pattern Analysis and Machine Intelligence. [All Versions]. Achieving human-like planning and control with multimodal observations in an open world is a key milestone for more functional generalist agents. Existing approaches can handle certain long-horizon tasks in an open…
MIT Press, 2018. [All Versions]. Richard Sutton's comprehensive book on reinforcement learning.
Journal of Artificial Intelligence Research, 1996. [All Versions]. Leslie Kaelbling's review on reinforcement learning.
2020. [All Versions]. Yaodong Yang's review on multi-agent reinforcement learning from the perspective of game theory.
Nature, 2015. [All Versions]. The original paper on solving Atari games via Deep Q-Network.
Artificial Intelligence, 1999. [All Versions]. The original paper on operation reinforcement learning.
Journal of Artificial Intelligence Research, 2017. [All Versions].
2018. [All Versions]. [Slides]. Sergey Levine's tutorial on treating reinforcement learning probabilisticly.
NeurIPS'19, 2019. [All Versions].
ICLR'21, 2021. [All Versions].
ICRA'18, 2018. [All Versions].
Journal of Logic and Computation, 2017. [All Versions].
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NeurIPS'21, 2021. [All Versions]. A formal treatment on the generalization problem in reinforcement learning.
ICLR'17, 2017. [All Versions].
Robotics and Automation Letters, 2021. [All Versions].
Journal of Machine Learning Research, 2017. [All Versions].
NeurIPS'21, 2021. [All Versions]. A formal treatment of tasks and rewards in reinforcement learning modeling.
ICML'15, 2015. [All Versions]. The original paper introducing TRPO, a method for optimizing control policies, with guaranteed monotonic improvement.
ICML'17, 2017. [All Versions]. The original paper on constrained reinforcement learning (safe reinforcement learning).
NeurIPS'19, 2019. [All Versions]. [Post].
ICML'21, 2021. [All Versions]. [Code].
Multi-disciplinary Conference on Reinforcement Learning and Decision Making'22, 2022. [All Versions]. Richard Sutton's perspective on the future directions of reinforcement learning research.
IJCAI'20, 2020. [All Versions].
ICML'21, 2021. [All Versions]. [Project].
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IJCAI'07, 2007. [All Versions]. A Bayesian account on classic inverse reinforcement learning.
ICLR'19, 2019. [All Versions].
AAAI'20, 2020. [All Versions].
ICML'21, 2021. [All Versions].
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Trends in Cognitive Sciences, 2021. [All Versions]. Yanchao Bi's review on neuroscience experiments on dual coding theory.
Neuron, 2020. [All Versions]. Illustrating language-derived and sensory-derived knowledge.
Cerebral Cortex, 2018. [All Versions].
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Journal of Visualized Experiments, 2017. [All Versions].
Nature Human Behavior, 2022. [All Versions].
National Science Review, 2025. [All Versions]. Advances in artificial intelligence (AI), particularly large language models (LLMs), have achieved remarkable success. This progress stems from ‘scaling laws’---performance improves with greater computation, data and model size. However, this paradigm…
Data Analysis, Classification, and Related Methods, 2000. [All Versions]. The original paper on symbolic regression.
Proceedings in Computational Statistics, 2006. [All Versions].
NeurIPS'18, 2018. [All Versions]. The original paper on neuro-symbolic probabilistic programming.
Journal of Artificial Intelligence Research, 2018. [All Versions]. The original paper for differential Inductive Logic Programming.
AAAI'17, 2017. [All Versions].
ICML'19, 2019. [All Versions].
NeurIPS'19, 2019. [All Versions]. [Slides]. [Code]. The original paper on Abductive Learning, a derivative-free approach for neuro-symbolic learning.
Science China Information Sciences, 2019. [All Versions].
IJCAI'21, 2021. [All Versions].
NeurIPS'21, 2021. [All Versions]. An approach for accelerating the convergence of Abductive Learning.
NeurIPS'19, 2019. [All Versions].
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CVPR'21, 2021. [All Versions].
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ICML'20, 2020. [All Versions].
CogSci'20, 2020. [All Versions].
ICLR'21, 2021. [All Versions].
Nature, 2016. [All Versions].
Science Advances, 2019. [All Versions]. A core challenge for both physics and artificial intelligence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle, functions of practical interest…
NeurIPS'19, 2019. [All Versions].
ICML'20, 2020. [All Versions].
NeurIPS'20, 2020. [All Versions].
ICML'20, 2020. [All Versions].
ICML'21, 2021. [All Versions]. Yoshua Bengio's perspective on slot attention model as a general production system.
NeurIPS'20, 2020. [All Versions].
ICLR'19, 2019. [All Versions].
ICLR'20, 2020. [All Versions].
NeurIPS'20, 2020. [All Versions].
NeurIPS'20, 2020. [All Versions].
ICLR'19, 2019. [All Versions].
ICLR'19, 2019. [All Versions].
NeurIPS'19, 2019. [All Versions].
ICLR'21, 2021. [All Versions].
IJCAI'21, 2021. [All Versions].
ICLR'21, 2021. [All Versions]. [Project].
Machine Learning, 2022. [All Versions]. A neuro-symbolic framework that integrates meta-policy learning in inductive logic programming.
CVPR'23, 2023. [All Versions]. VISPROG, a neuro-symbolic approach to solving complex and compositional visual tasks given natural language instructions, using the in-context learning ability of large language models to generate python-like modular programs, which are then executed to get both the…
ICDM'20, 2020. [All Versions]. [Preprint]. In many practical tasks, there are usually two kinds of common information: cheap unlabeled data and domain knowledge in the form of symbols. There are some attempts using one single information source, such as semi-supervised learning and abductive…
Proceedings of the National Academy of Sciences, 2022. [All Versions]. A Bayesian framework for combining the predictions and different types of confidence scores from humans and machines.
Science Robotics, 2019. [All Versions]. [Preprint]. The ability to provide comprehensive explanations of chosen actions is a hallmark of intelligence. Lack of this ability impedes the general acceptance of AI and robot systems in critical tasks. This paper examines what forms of explanations best…
CVPR XAI Workshop'19, 2019. [All Versions]. This work presents a new explainable AI (XAI) framework aimed at increasing justified human trust and reliance in the AI machine through explanations. The authors pose explanation as an iterative communication process, i.e. dialog, between the machine…
AAAI'20, 2020. [All Versions].
iScience, 2022. [All Versions]. This work proposes CX-ToM, short for counterfactual explanations with theory-of-mind, a new explainable AI (XAI) framework for explaining decisions made by a deep convolutional neural network (CNN). In contrast to the current methods in XAI that generate…
Nature Machine Intelligence, 2023. [All Versions]. Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners…
Machine Learning, 2018. [All Versions]. During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later…
Machine Learning, 2021. [All Versions]. Given the recent successes of Deep Learning in AI there has been increased interest in the role and need for explanations in machine learned theories. A distinct notion in this context is that of Michie’s definition of ultra-strong machine learning (USML).…
IJCAI'17, 2017. [All Versions]. [Project]. This paper proposes gcForest, a decision tree ensemble approach with performance highly competitive to deep neural networks in a broad range of tasks. In contrast to deep neural networks which require great effort in hyper-parameter tuning, gcForest is…
ICLR'21, 2021. [All Versions]. [Code]. Machine learning applications such as finance and medicine demand accurate and justifiable predictions, barring most deep learning methods from use. In response, previous work combines decision trees with deep learning, yielding models that (1) sacrifice…
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CVPR'17, 2017. [All Versions]. [Project]. [Dataset: Places365]. The original paper on visualizing the class activation maps to explain convolutional neural networks.
Proceedings of the National Academy of Sciences, 2020. [All Versions]. David Bau's review on network dissection for discriminative and generative models.
Distill, 2020. [All Versions]. A perspective on treating neural networks as circuits.
NeurIPS'20, 2020. [All Versions]. [Project]. A concept-composition version of network dissection.
NeurIPS'19, 2019. [All Versions].
Proceedings of the National Academy of Sciences, 2019. [All Versions].
ICLR'21, 2021. [All Versions]. [Code & Data]. [Project]. A perspective on image background provides strong clue for foreground classification.
NeurIPS'18, 2018. [All Versions]. Maching the learned pattern of neurons in different neural networks.
Nature Communications, 2020. [All Versions].
Plato Stanford. A computational philosophy account on Embodied Cognition, which emphasizes the significance of an agent's physical body in cognitive abilities.
Plato Stanford. A computational philosophy account on mind externalism, a long-term debate about the boundary of embodied intelligence.
Human Factors, 1988. [All Versions]. The original idea of investigating huamn tool use in problem solving.
Cambridge University Press, 1993. [All Versions]. A classic perspective correlating human tool use with the evolution of civilization.
Analysis, 1998. [All Versions]. The original paper on the debate of mind externalism.
Trends in Cognitive Sciences, 2004. [All Versions]. A neuroscience account of human tool use.
Current Biology, 2007. [All Versions]. A piece of evidence that intelligent animals can take advantage of matatools to make tools for problem solving.
Psychological Science, 2010. [All Versions].
Behavioral and Brain Sciences, 2012. [All Versions].
Frontiers in Psychology, 2013. [All Versions].
Philosophical Transactions of the Royal Society B: Biological Sciences, 2013. [All Versions].
Neuropsychologia, 2014. [All Versions].
Psychological Review, 2016. [All Versions]. A classic review on human tool use and affordance.
CogSci'21, 2021. [All Versions].
CVPR'15, 2015. [All Versions]. [Project]. The original paper introducing affordance and physically-grounded tool use into computer vision.
Science Robotics, 2021. [All Versions].
Journal of Neuroscience, 2021. [All Versions].
CogSci'21, 2021. [All Versions].
ICRA'05, 2005. [All Versions].
ILP'12, 2012. [All Versions].
Autonomous Robots, 2017. [All Versions].
RSS'19, 2019. [All Versions].
Science Robotics, 2017. [All Versions]. Humanoids represent one of the ultimate goals of robotics: to synthesize advances from many disciplines.
RSS'20, 2020. [All Versions]. This paper presents a unified representation for actionable spatial perception: 3D Dynamic Scene Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (e.g. objects, walls, rooms), and edges represent relations (e.g. inclusion,…
Nature Machine Intelligence, 2025. [All Versions]. Completing complex tasks in unpredictable settings challenges robotic systems, requiring a step change in machine intelligence. Sensorimotor abilities are considered integral to human intelligence. Thus, biologically inspired machine intelligence…
IEEE Transactions on Robotics, 2023. [All Versions]. Inspired by Alan Turing's idea of a child machine, this article introduces the formal definition of a robotic baby, an integrated system with minimal world knowledge at birth, capable of learning incrementally and interactively, and adapting to…
Science, 2012. [All Versions]. A classic paper correlating biological trade-offs with the evolution of pareto optimality.
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IEEE Transactions on Systems, Man, and Cybernetics, 2008. [All Versions]. A comprehensive review on the application of pareto optimality to multiobjective machine learning.
Nature, 2019. [All Versions]. A Bayesian phylogenetic analysis on two competing hypotheses of the origin of the Sino-Tibetan language family suggests that the initial expansion of Sino-Tibetan languages occurred approximately 4,000–6,000 years before present (BP; taken as AD 1950) in the Yellow…
Nature, 2021. [All Versions]. [Nature News]. A triangulation of linguistic, archaeological and genetic data suggests that the Transeurasian language family originated in a population of grain farmers in China around 9,000 years ago, and that agriculture underpinned its spread.
Science, 2023. [All Versions]. [Preprint]. This work supports a unified foundation for human lexical creativity underlying both the fleeting products of individual ontogeny and the evolutionary products of phylogeny across languages.
Journal of the American Statistical Association, 1996. [All Versions]. The original paper on Instrumental Variables for natural sociology studies.
Annual Review of Psychology, 2017. [All Versions]. A comprehensive review of the quantitative analysis techniques for behavioral studies.
Oxford Bulletin of Economics and Statistics, 2010. [All Versions]. The original method for testing U-shape relation from the data, which is distinctive from the quadratic regression test.
Advances in Methods and Practices in Psychological Science, 2018. [All Versions]. An alternative method to test the statistical significance of U-shaped relationships.
Open Science Foundation Preprints. [All Versions]. A white paper on scaling up social, behavioral, and econimic experiments.
Brain and Behavioral Sciences, 2010. [All Versions]. The original paper on rethinking and tackling the sample bias in behaivoral studies, where most subjects are drawn from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies.
Proceedings of the National Academy of Sciences, 2020. [All Versions]. The statistical and ecological basis for scaling up behavioral studies.
Science, 2021. [All Versions].
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Nature, 2021. [All Versions].
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KDD'15, 2015. [All Versions]. Large scale user study in the development of the recommendations system by Pinterest.
Behavior Research Methods, 2022. [All Versions]. Model-based strategy identification.
CogSci'16, 2016. [All Versions]. A behavioral study for the 20 questions game.
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Proceedings of the National Academy of Sciences, 2015. [All Versions].
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CogSci'14, 2014. [All Versions].
CogSci'19, 2019. [All Versions].
CogSci'21, 2021. [All Versions].
ICML'18, 2018. [All Versions].
Current Opinion in Behavioral Sciences, 2019. [All Versions].
Nature Communications. 2019. [All Versions].
Nature Neuroscience, 2022. [All Versions].
Wikipedia. Wikipedia on the Implicit Association Test, a controversial assessment intended to detect subconscious associations between mental representations of objects (concepts) in memory.
Journal of Personality and Social Psychology, 1998. [All Versions]. The original paper introducing the Implicit Association Test.
Zeitschrift für Experimentelle Psychologie, 2001. [All Versions]. The 3rd year review for the IAT.
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Personality and Social Psychology Bulletin, 2005. [All Versions].
Nature Neuroscience, 2002. [All Versions]. A classic review on the early applications of Virtual Reality to behavioral studies.
Journal of Media Psychology, 2009. [All Versions].
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Media Psychology, 2016. [All Versions]. A meta-analysis on the extent to which technologies need to be immersive in order to generate a sense of presence.
VR'23, 2023. [All Versions].
VRST'17, 2017. [All Versions]. This paper proposes the use of Domain-Specific Languages (DSLs) to ease the description and generation of VR experiments, thus letting experiment designers focus on their core tasks: designing, conducting, and reporting experiments.
UIST'24, 2024. [All Versions]. Procedural content generation (PCG), the process of algorithmically creating game components instead of manually, has been a common tool of game development for decades. Recent advances in large language models (LLMs) enable the generation of game behaviors based on…
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ICML'17, 2017. [All Versions]. [Post]. Chelsea Finn's original paper on Model-Agnostic Meta-Learning (MAML).
NeurIPS'18, 2018. [All Versions]. A Bayesian account on MAML.
ICLR'20, 2020. [All Versions]. The milestone paper on context Meta-RL.
ICML'19, 2019. [All Versions].
ICLR'21, 2021. [All Versions].
ICLR'17, 2017. [All Versions].
NeurIPS'21, 2021. [All Versions].
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Current Directions in Psychological Science, 2012. [All Versions]. A Marr's paradigm account on probabilistic models.
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ICLR'20 Bridging AI and Cognitive Science Workshop, 2020. [All Versions]. A Marr's paradigm account on machine learning.
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Psychologische Forschung, 1967. [All Versions]. Wolfgang Köhler's review on Gestalt psychology.
Scandinavian Journal of Psychology, 1984. [All Versions].
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Frontiers in Psychology, 2016. [All Versions].
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Plato Stanford. A computational philosophy account on Bounded Rationality, an elementary hypothesis of human intelligence in psychology and ecology.
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Trends in Cognitive Sciences, 2003. [All Versions]. [Preprint]. The original paper on ``switch cost'', where subjects' responses are substantially slower and, usually, more error-prone immediately after a task switch.
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Trends in Cognitive Sciences, 2020. [All Versions]. [Preprint]. Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. The author argues that we can understand human intelligence, and the…
Nature Human Behavior, 2022. [All Versions]. Evidences support that people have some of the foundations for 'intuitive power analyses', which help people use intuitive statistical reasoning and metacognitive strategies to estimate how much information they might need to solve different…
Annual Review of Control, Robotics, and Autonomous Systems, 2022. [All Versions]. The review focuses on how cognitive science can provide forward models of human decision-making and inverse models of how humans think about others’ decision-making. The authors highlight relevant recent…
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University of Chicago Press: Chicago, 1970. [All Versions]. Thomas Kuhn's original book on the emergence and the shift of scientific paradigms.
Sociological Theory, 2008. [All Versions]. A philosophical account on the definition of "theory" in social science (also can be generalized to natural science).
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Proceedings of the National Academy of Sciences, 2004. [All Versions]. A first step in identifying the content of a document is determining which topics that document addresses. This paper describes a generative model for documents, in which each document is generated by choosing a distribution…
Proceedings of the National Academy of Sciences, 2017. [All Verisions]. An analysis of bias patterns and risk factors in science.
Proceedings of the National Academy of Sciences, 2021. [All Verisions]. An analysis of why too many papers published each year in a field can lead to stagnation rather than advance.
ACM SIGCHI'16, 2016. [All Versions]. This essay contributes a meta-scientific account of human-computer interaction (HCI) research as problem-solving. We build on the philosophy of Larry Laudan, who develops problem and solution as the foundational concepts of science. We argue that most HCI…
Nature Communications, 2024. [All Versions]. This paper presents a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models can be fine-tuned to extract useful records of complex scientific knowledge. The authors test three…
Nature Communications, 2020. [All Versions]. This paper presents a method to convert unstructured experimental procedures written in English to structured synthetic steps (action sequences) reflecting all the operations needed to successfully conduct the corresponding chemical reactions.
Nature Communications, 2021. [All Versions]. This paper presents data-driven models for predicting the entire sequence of synthesis steps starting from a textual representation of a chemical equation, for application in batch organic chemistry.
Nature Communications, 2023. [All Versions]. This paper introduces a transformer model for automated synthesis protocol analysis in catalyst discovery, exemplified using single-atom heterogeneous catalysts (SACs), a rapidly expanding catalyst family. The model adeptly converts SAC protocols into…
Scientific Reports, 2025. [All Versions]. To enhance aircraft fault diagnosis efficiency, this paper proposes HybridRAG, an intelligent-guided troubleshooting framework that integrates knowledge graphs and large language models (LLMs). Unlike conventional retrieval-augmented generation (RAG)…
Scientific Reports, 2025. [All Versions]. Recent advancements in large language models (LLMs) have significantly enhanced text generation across various sectors; however, their medical application faces critical challenges regarding both accuracy and real-time responsiveness. To address these dual…
Meta AI, 2022. [All Versions]. A large language model trained on large-scale scientific corpus.
NAACL'22, 2022. [All Versions].
ACL'21 Demo Track, 2021. [All Versions]. A tool for constructing and visualizing the knowledge graph of a query keyword in literature retrieving.
IEEE Transactions on Visualization and Computer Graphics, 2016. [All Versions].
IEEE Transactions on Visualization and Computer Graphics, 2019. [All Versions].
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Written Communication, 1998. [All Versions]. A behaviorial study revealing the argument structures exploited by people in argumentative writing.
The Knowledge Engineering Review, 2006. [All Versions]. The original paper introducing the Argument Interchange Format (AIF) framework for argumentation analysis.
AAAI'12, 2012. [All Versions]. The original paper introducing the Information Anchoring Theory (IAT) as an alternate for AIF.
American Psychologist, 1986. [All Versions]. Susan Carey's review on cognitive-science-based methodologies for science education research.
ACL'23, 2023. [All Versions]. Scientific research is inherently shaped by its authors’ perspectives, influenced by various factors such as their personality, community, or society. Junior researchers often face challenges in identifying the perspectives reflected in the existing literature and…
Science, 2014. [All Versions].
Nature Chemistry, 2024. [All Versions]. This perspective article formulates eight principles to improve data management in scientific publications relating to data standardization, reproducibility and evaluation, and encourage scientists to go beyond current publication standards.
Nature Human Behavior, 2017. [All Versions].
Nature, 2016. [All Versions].
PLoS Medicine, 2014. [All Versions].
Nature, 2021. [All Versions]. This interviewing paper introduces five ways to increase the reproducibility of experimental protocols: (i) documenting protocols as the experiment goes; (ii) providing video illustrations in addition to written protocols; (iii) using electronic lab notebooks (ELNs)…
PLoS Biology, 2017. [All Versions]. [Nature Methods Correspondence]. [EDA Website]. The EDA is a web-based tool that guides the in vivo researcher through the experimental design and analysis process, providing automated feedback on the proposed design and generating a graphical summary that aids…
Science, 2018. [All Versions]. [Preprint]. This paper describes a plug-and-play, continuous-flow chemical synthesis system that mitigates this challenge with an integrated combination of hardware, software, and analytics. The system software controls the user-selected reagents and unit operations…
Science, 2020. [All Versions]. [Preprint]. [XDL Documentation]. [XDL Schema Database]. This paper reports a software platform that uses natural language processing to translate the organic chemistry literature directly into editable code, which in turn can be compiled to drive automated synthesis…
Science, 2022. [All Versions]. [Preprint]. This paper presents an automatically executable chemical reaction database of 100 molecules representative of the range of reactions found in contemporary organic synthesis. The chemical reaction codes or χDLs for the reactions have been stored in a…
Journal of the American Chemical Society (Au), 2021. [All Versions]. This paper describes a standard hardware (the chemical processing programming architecture --- the ChemPU) to encompass all chemical synthesis, an approach which unifies all chemistry automation strategies, from solid-phase…
Nature Chemistry, 2022. [All Versions]. [Preprint]. This paper presents a portable suitcase-sized chemical synthesis platform containing all the modules required for synthesis and purification. The system uses a chemical programming language coupled to a digital reactor generator to produce…
Nature, 2020. [All Versions]. [Preprint]. This work uses a mobile robot to search for improved photocatalysts for hydrogen production from water. The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian…
Nature, 2023. [All Versions]. This paper introduces the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of…
Nature, 2017. [All Versions]. The emergence of connected instruments and equipment promises to untether researchers from the laboratory --- letting them fine-tune experiments and analyse data remotely.
Nature Communications, 2024. [All Versions]. This work employs ontologies to capture data and material flows in design-make-test-analyse cycles, utilising autonomous agents as executable knowledge components to carry out the experimentation workflow. Data provenance is recorded to ensure its…
Chemical Science, 2021. [All Versions]. This perspective provides an overview of the current state of automation of synthetic chemistry at the benchtop scale with a particular emphasis on core considerations and the ensuing challenges of deploying a system. The authors aim to reframe automation as…
Trends in Chemistry, 2023. [All Versions]. This perspective article provides essential insights into the decision-making process for choosing automation platforms, highlighting the suitability of fixed automation for standardized tasks and the strategic use of flexible automation in dynamic…
Matter, 2022. [All Versions]. This paper proposes SDL-Demo: a low-cost “Hello, World!” for self-driving laboratories that combines “Hello, World!” tasks from electronics, physics-based simulations, and optimization. SDL-Demo is modular and extensible, making it an ideal candidate for low-cost…
eLife, 2022. [All Versions]. This paper develops a robotic AI system with a batch Bayesian optimization algorithm that autonomously induces the differentiation of induced pluripotent stem cell-derived retinal pigment epithelial (iPSC-RPE) cells. From 200 million possible parameter combinations,…
Nature Computational Science, 2025. [All Versions]. Autonomous synthesis laboratories promise to streamline the plan–make–measure–analyze iteration loop. Here, the authors comment on the barriers in the field, the promise of a human on-the-loop approach, and strategies for optimizing…
Nature Communications, 2023. [All Versions]. Closed-loop, autonomous experimentation enables accelerated and material-efficient exploration of large reaction spaces without the need for user intervention. However, autonomous exploration of advanced materials with complex, multi-step processes and…
Nature, 2023. [All Versions]. A review article that examines breakthroughs over the past decade that include self-supervised learning, which allows models to be trained on vast amounts of unlabelled data, and geometric deep learning, which leverages knowledge about the structure of scientific data…
Journal of the American Chemical Society, 2024. [All Versions]. The development of AI synthesis planners trained solely on reaction-example-data has stagnated and is not on par with the performance of “hybrid” algorithms combining AI with expert knowledge. This Perspective examines possible causes…
Microsoft Research AI4Science, 2023. [All Versions]. [Project]. A survey on the performance of LLMs within the context of scientific discovery, focusing on GPT-4.
Nature, 2026. [All Versions]. Rare diseases affect more than 300 million people worldwide, yet timely and accurate diagnosis remains an urgent challenge. Patients often endure a prolonged ‘diagnostic odyssey’ exceeding 5 years, marked by repeated referrals, misdiagnoses and unnecessary…
Nature, 2026. [All Versions]. The automation of science is a long-standing ambition in artificial intelligence (AI) research. Although the community has made substantial progress in automating individual components of the scientific process, a system that autonomously navigates the entire research…
Science Advances, 2019. [All Versions]. In the process of finding high-performance materials for organic photovoltaics (OPVs), it is meaningful if one can establish the relationship between chemical structures and photovoltaic properties even before synthesizing them. This work first establishes a…
Scientific Reports, 2018. [All Versions]. The design of novel proteins has many applications but remains an attritional process with success in isolated cases. Meanwhile, deep learning technologies have exploded in popularity in recent years and are increasingly applicable to biology due to the…
Nature, 2021. [All Versions]. This paper provides the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. This approach is a canonical application of observation- and explanation- based method for…
Nature, 2023. [All Versions]. [Nature News]. This work studies Bayesian optimization algorithms to investigate how artificial intelligence (AI) might decrease the cost of developing complex semiconductor chip processes. In particular, this work create a controlled virtual process game to…
Nature, 2023. [All Versions]. This paper presents RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6…
Nature, 2023. [All Versions]. This paer introduces an artificial-intelligence-based method for accurate, medium-range global weather forecasting. It shows that three-dimensional deep networks equipped with Earth-specific priors are effective at dealing with complex patterns in weather data, and…
Science, 2023. [All Versions].
Nature, 2023. [All Versions].
Nature, 2023. [All Versions]. An artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs complex experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation.
Nature Machine Intelligence, 2023. [All Versions]. [Preprint]. This paper introduces ChemCrow, an LLM chemistry agent designed to accomplish tasks across organic synthesis, drug discovery and materials design. By integrating 18 expert-designed tools and using GPT-4 as the LLM, ChemCrow augments…
Cell, 2024. [All Versions]. The authors envision “AI scientists” as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the…
Nature Communications, 2025. [All Versions]. [Project]. Functional proteomics provides critical insights into cancer mechanisms, facilitating the discovery of novel biomarkers and therapeutic targets. The authors have developed a comprehensive cancer functional proteomics resource using reverse…
Nature, 2025. [All Versions]. Science frequently benefits from teams of interdisciplinary researchers, but many scientists do not have easy access to experts from multiple fields. Although large language models (LLMs) have shown an impressive ability to aid researchers across diverse domains,…
EMNLP'23, 2023. [All Versions]. [Project]. This paper presents an automatic evaluation framework for the task of planning experimental protocols, and introduces BioProt: a dataset of biology protocols with corresponding pseudocode representations.
Science China Information Sciences, 2025. [All Versions]. Conventional biomedical research is increasingly labor-intensive due to the exponential growth of scientific literature and datasets. Artificial intelligence (AI), particularly large language models (LLMs), has the potential to…
Nature Communications, 2024. [All Versions]. Autonomous reaction network exploration algorithms offer a systematic approach to explore mechanisms of complex chemical processes. However, the resulting reaction networks are so vast that an exploration of all potentially accessible intermediates is…
Nature Communications, 2025. [All Versions]. Anode-free or ‘zero-excess’ lithium metal batteries offer high energy density compared to current lithium-ion batteries but require electrolyte innovation to extend cycle life. Due to the lack of universal design principles, electrolyte development for…
Nature Communications, 2024. [All Versions]. The automatic analysis of patent publications has potential to accelerate research across various domains, including drug discovery and material science. Within patent documents, crucial information often resides in visual depictions of molecule…
Nature Machine Intelligence, 2025. [All Versions]. Large language models (LLMs) are a form of artificial intelligence system encapsulating vast knowledge in the form of natural language. These systems are adept at numerous complex tasks including creative writing, storytelling, translation,…
Nature Communications, 2023. [All Versions]. Retrosynthesis planning, the process of identifying a set of available reactions to synthesize the target molecules, remains a major challenge in organic synthesis. Recently, computer-aided synthesis planning has gained renewed interest and various…
2023. [All Versions]. ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, the authors instead adopt the following domain adaptation techniques: domain-adaptive…
Nature Communications, 2021. [All Versions]. This paper addresses the problem of new Single-atom-alloy catalysts (SAACs) discovery by applying a compressed-sensing data-analytics approach parameterized with density-functional inputs.
Proceedings of the National Academy of Sciences, 2021. [All Versions].
Bioprocess and Biosystems Engineering, 2016. [All Versions].
Cell Reports Medicine, 2021. [All Versions]. 3D visualization technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) have gained popularity in the recent decade. Digital extended reality (XR) technologies have been adopted in various domains ranging from…
Nature Medicine, 2019. [All Versions]. The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessments demonstrate considerable variability and many regions of the world lack access to trained pathologists.…
IEEE Transactions on Knowledge and Data Engineering, 2023. [All Versions].
EMNLP'20, 2020. [All Versions]. Generating answers to legal questions, analyze contracts, and summarizing legal documents, making legal knowledge more accessible to non-experts.
Bioinformatics, 2020. [All Versions]. Answering medical questions, identifying relevant clinical trials, and diagnosing diseases based on symptoms, making medical information more accessible to the general public.
IJCAI'20, 2020. [All Versions]. Predicting stock market trends, analyzing financial documents, and generating summaries of economic news articles, helping to disseminate financial knowledge.
EMNLP'19, 2019. [All Versions]. Searching and synthesizing scientific literature, aiding researchers in hypothesis generation, and assisting with experimental design, making scientific knowledge more accessible.
EMNLP'20, 2020. [All Versions]. Completing code, generating programming documentation, and providing technical support, making programming knowledge more accessible to non-experts.
Wikipedia. Wikipedia on Theory of Mind (ToM), a cognitive capability that estimating others' goal, belief, and desire.
Plato Stanford.
Plato Stanford.
Trends in Cognitive Sciences, 2016. [All Versions]. [Preprint]. This review article proposes that human social cognition is structured around a basic understanding of ourselves and others as intuitive utility maximizers: from a young age, humans implicitly assume that agents choose goals and…
Trends in Cognitive Sciences, 2022. [All Versions]. [Preprint]. A perspective on understanding Theory of Mind through planning that consists of abstract structured causal representations and supports efficient search and selection from innumerable possible actions. Planning requires that Theory of…
Cognition, 2009. [All Versions]. [Appendix]. The original paper on Inverse Planning, a computational implementation of Theory of Mind. Humans are adept at inferring the mental states underlying other agents’ actions, such as goals, beliefs, desires, emotions and other thoughts. This paper proposes…
CogSci'11, 2011. [All Versions]. [Preprint]. This paper presents a computational framework for understanding Theory of Mind (ToM): the human capacity for reasoning about agents’ mental states such as beliefs and desires. The proposed Bayesian model of ToM (or BToM) expresses the predictive model…
CogSci'20, 2020. [All Versions].
Trends in Cognitive Sciences, 2016. [All Versions]. A perspective on human probabilistic modeling without explicit probabilistic computation.
Nature Human Behavior, 2017. [All Versions]. [Preprint]. This paper presents a model of core mentalizing computations: inferring jointly an actor’s beliefs, desires and percepts from how they move in the local spatial environment. The proposed Bayesian theory of mind (BToM) model is based on…
ICML'18, 2018. [All Versions]. Theory of mind (ToM) broadly refers to humans’ ability to represent the mental states of others, including their desires, beliefs, and intentions. This work proposes a Theory of Mind neural network --- a ToMnet --- which uses meta-learning to build such models of the…
Current Opinion in Behavioral Sciences, 2019. [All Versions]. This paper reviews the idea that Theory of Mind --- humans' ability to reason about other people's mental states --- can be formalized as inverse reinforcement learning. Under this framework, expectations about how mental states produce…
Topics in Cognitive Science, 2019. [All Versions]. This paper proposes an intuitive theory framework to studying affective cognition—how humans reason about emotions—and derive a taxonomy of inferences within affective cognition. Using this taxonomy, the authors review formal computational…
Cognitive Psychology, 2021. [All Versions]. [Project]. This paper presents a formal theory of the Naïve Utility Calculus as a probabilistic generative model, which highlights the role of cost and reward tradeoffs in a Bayesian framework for action-understanding. The model predicts with…
ICML'21, 2021. [All Versions]. Inspired by cognitive development studies on intuitive psychology, this paper presents a benchmark consisting of a large dataset of procedurally generated 3D animations, AGENT (Action, Goal, Efficiency, coNstraint, uTility), structured around four scenarios (goal…
Annual Review of Psychology, 2021. [All Versions]. Experimental games model situations in which the future outcomes of individuals and groups depend on their own choices and on those of other (groups of) individuals. Games are a powerful tool to identify the neural and psychological mechanisms…
AAAI'19, 2019. [All Versions]. Towards the goal of building machine-learning algorithms with human-like social intelligence, this paper develops a generative model of multiagent action understanding based on a novel representation for these latent relationships called Composable Team Hierarchies…
Emotion, 2019. [All Versions].
Cognition, 2013. [All Versions].
Neuron, 2013. [All Versions].
Scientific Report, 2018. [All Versions].
Journal of Experimental Psychology, 2020. [All Versions].
Proceedings of the National Academy of Sciences, 2020. [All Versions].
CVPR'21, 2021. [All Versions]. [Preprint]. This paper incorporates different nonverbal communication cues (e.g., gaze, human poses, and gestures) to represent, model, learn, and infer agents' mental states from pure visual inputs. Crucially, such a mental representation takes the agent's belief…
Science, 2017. [All Versions]. A piece of evidence for children's capability on ToM.
Proceedings of the National Academy of Sciences, 2019. [All Versions].
NeurIPS'21, 2021. [All Versions].
CVPR'21, 2021. [All Versions]. A large-scale database on human intentionally-posted images on social media.
CogSci'20, 2020. [All Versions].
AAAI'21, 2021. [All Versions]. [Project].
ICLR'21, 2021. [All Versions].
CogSci'24, 2024. [All Versions]. This work eveloped a comprehensive theoretical framework for social dynamics and introduced two evaluation tasks: Inverse Reasoning (IR) and Inverse Inverse Planning (IIP). The approach also encompassed a computational model based on recursive Bayesian inference,…
Plato Stanford. A computational philosophy account on Metaphor, a poetically or rhetorically ambitious use of words, a figurative as opposed to literal use.
Plato Stanford. A computational philosophy account on Analogy, a comparison between two objects, or systems of objects, that highlights respects in which they are thought to be similar.
MIT Press, 1985. [All Versions]. A cognitive account on Metaphor.
Artificial Intelligence, 1989. [All Versions]. A computational implementation of analogy.
American Psychologist, 1997. [All Versions]. A perspective unifying analogy and similarity judgement.
Psychological Review, 2022. [All Versions]. A comprehensive review on the perspective of treating analogy as cross-domain generalization.
Proceedings of the National Academy of Sciences, 2019. [All Versions]. Analogy feature in language models.
ICML'19, 2019. [All Versions]. Explaining the analogy capability in word embeddings.
ACL'17, 2017. [All Versions].
ICCC'15, 2015. [All Versions].
ICML'13, 2013. [All Versions]. The first application of analogy to machine learning.
NeurIPS'15, 2015. [All Versions].
CVPR'19, 2019. [All Versions].
Artificial Intelligence, 2019. [All Versions]. A mathematical account on analogy.
ICLR'19, 2019. [All Versions].
ACL'20, 2020. [All Versions].
CogSci'20, 2020. [All Versions].
CogSci'21, 2021. [All Versions]. A human-deep-learning comparison on similarity judgement.
CogSci'22, 2022. [All Versions]. A piece of evidence that understanding metaphors is capable for different cognitive development phases.
Psychological Science, 1990. [All Versions].
Wikipedia. Wikipedia on causality, which is influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause.
Plato Stanford. A computational philosophy account on Causal models, which are mathematical models representing causal relationships within an individual system or population.
Plato Stanford. A computational philosophy account on causal theories of mental content, which attempts to explain how thoughts can be about things.
Journal of the American Statistical Association, 1996. [All Versions]. The original paper on Instrumental Variables for natural sociology studies.
Journal of Experimental Psychology, 1992. [All Versions]. Experimental evidences for distincting causality and association.
The Oxford Handbook of Cognitive Psychology, 2013. [All Versions].
1998. Judea Pearl's tutorials on causal reasoning with operations on Bayesian networks.
Communications of the ACM, 2019. [All Versions]. Judea Pearl's review on causal inference in probabilistic graph models.
Proceedings of the IEEE, 2021. [All Versions]. Yoshua Bengio's review on the perspective of treating causal inference as a representation learning problem.
Psychological Review, 2009. [All Versions]. Thomas Griffiths' review on causal Bayesian theory induction.
AAAI'20, 2020. [All Versions]. A computatinoal account on causal transfer.
Cognitive Science, 2010. [All Versions].
CogSci'15, 2015. [All Versions].
Psychological Science, 2017. [All Versions].
2021. [All Versions].
Computational Brain & Behavior, 2022. [All Versions]. [Preprint]. How do people decide how general a causal relationship is, in terms of the entities or situations it applies to? What features do people use to decide whether a new situation is governed by a new causal law or an old one? How can…
Science, 2006. [All Versions]. A piece of evidence for the capability of causal reasoning in intelligent animals.
Proceedings of the Royal Society B: Biological Sciences, 2009. [All Versions]. A piece of evidence for the capability of causal reasoning in intelligent animals.
Cognition, 1987. [All Versions].
GitHub. A reading list on intuitive physics, maintained actively by Shiqian Li.
Trends in Cognitive Sciences, 2018. [All Versions]. Hongjing Lu's review on intuitive physics.
Proceedings of the National Academy of Sciences, 2013. [All Versions]. [Appendix]. The first attempt to computationally simulate intuitive physics.
Proceedings of the National Academy of Sciences, 2016. [All Versions]. A piece of evidence for the functional part of intuitive physics in human brain.
Trends in Cognitive Sciences, 2017. [All Versions]. Tomer Ullman's review on simulation-based intuitive physics.
Cognitive Psychology, 2017. [All Versions].
Cognitive Psychology, 2021. [All Versions]. Ernest Davis's perspective against intuitive physics, that physcial reasoning is logical reasoning instead of intuition.
Cognitive Neuropsychology, 2022. [All Versions].
Nature Human Behavior, 2022. [All Versions]. A machine-learning dataset designed to evaluate conceptual understanding of intuitive physics, adopting the violation-of-expectation (VoE) paradigm from developmental psychology; a deep-learning system that learns intuitive physics directly from visual…
NeurIPS'19, 2019. [All Versions]. A benchmark for AI physical reasoning.
Nature Machine Intelligence, 2023. [NMI Challenge]. An interactive benchmark for AI physical reasoning.
Morgan Kaufmann, 1990. [All Versions]. A classic book on commonsense knowledge.
FSTTCS, 1990. [All Versions]. The original paper on visual commonsense.
Communications of the ACM, 2015. [All Versions]. Gary Marcus's review on commonsense knowledge in AI.
CVPR'19, 2019. [All Versions]. [Project].
AAAI'20, 2020. [All Versions].
CVPR'20, 2020. [All Versions].
ICLR'20, 2020. [All Versions]. Abductive commonsense reasoning on large language models.
ECCV'20, 2020. [All Versions].
ECCV'22, 2022. [All Versions]. [Preprint]. This paper presents Sherlock, an annotated corpus of 103K images for testing machine capacity for abductive reasoning beyond literal image contents. The corpus construction process adopts a free-viewing paradigm: participants first observe and identify…
NAACL'24, 2024. [All Versions]. This paper explores the task of uncommonsense abductive reasoning. Given a piece of context with an unexpected outcome, this task requires reasoning abductively to generate an explanation that makes the unexpected outcome more likely in the context.
EMNLP'20, 2020. [All Versions]. A perspective on the furture of computational linguistics research---commonsense-driven and embodied language.
EMNLP'21, 2021. [All Versions].
NeurIPS'23, 2023. [All Versions]. [Project].
wikiHow.com. wikiHow is on website hosting step-by-step "How-to" procedural instructions across various domains and topics.
The World Avatar™. A large-scale dynamic knowledge graph connecting concepts with relations to digitalize molecules, buildings, cities, and countries.
Communications of the ACM, 1995. [All Versions]. The first attempt to build large-scale commonse knoweldgebase from human knowledge.
AAAI'17, 2017. [All Versions]. Latest version of ConceptNet.
Proceedings of AAAI Spring Symposium on Acquiring (and Using) Linguistic (and World) Knowledge for Information Access, 2002. [All Versions]. The first attempt for acquring commonsense knowlege from humans' activities on the internet.
OTM Confederated International Conferences'02, 2002. [All Versions]..
CHI'06, 2006. [All Versions].
Communications of the ACM, 2008. [All Versions].
AAAI'14, 2014. [All Versions].
IEEE Transactions on Visualization and Computer Graphics, 2023. [All Versions]. This paper presents Visual Concept Programming, a first-of-its-kind visual analytics approach of using visual concepts to program image data at scale while requiring a few human efforts.
Plato Stanford. A computational philosophy account on Inductive Logic, which is a logic of evidential support.
Plato Stanford. A computational philosophy account on First-order Model Theory, which is a branch of mathematics that deals with the relationships between descriptions in first-order languages and the structures that satisfy these descriptions.
Plato Stanford. A computational philosophy account on Paraconsistent Logic, where any logic is paraconsistent as long as it is not explosive.
Plato Stanford. A computational philosophy account on Logical Consequence, which is about the relation between premises and conclusions in valid arguments.
Plato Stanford. A computational philosophy account on Logic Pluralism, which is the view that there is more than one correct logic.
Plato Stanford. A computational philosophy account on the emergence of first-order logic, mainly about first-order logic is natural retrospect.
Plato Stanford.
Foundations and Trends in Programming Languages, 2017. [All Versions]. Sumit Gulwani's comprehensive review on program synthesis.
IJCAI'83, 1983. [All Versions]. The original paper on second-order metarules.
ILP'01, 2001. [All Versions].
Machine Learning, 2014. [All Versions]. Stephen Muggleton's original paper on Meta-Interpretive Learning (MIL).
IJCAI'15, 2015. [All Versions].
IJCAI'16, 2016. [All Versions].
ILP'18, 2018. [All Versions].
Machine Learning, 2018. [All Versions].
Machine Learning, 2018. [All Versions].
Machine Learning, 2019. [All Versions].
Machine Learning, 2019. [All Versions].
IJCAI'19, 2019. [All Versions].
New Generation Computing, 2019. [All Versions].
AAAI'20, 2020. [All Versions].
IJCAI'20, 2020. [All Versions].
Journal of Artificial Intelligence Research, 2020. [All Versions]. A 30-year comprehensive review on Inductive Logic Programming.
Machine Learning, 2020. [All Versions].
IJCAI'20, 2020. [All Versions].
Machine Learning, 2021. [All Versions].
Artificial Intelligence, 2004. [All Versions].
IJCAI'16, 2016. [All Versions].
Journal of The London Mathematical Society-second Series, 2005. [All Versions].
ICML'20, 2020. [All Versions].
NeurIPS'21, 2021. [All Versions].
CogSci'21, 2021. [All Versions].
2021. [All Versions]. This paper explores the limits of the current generation of large language models for program synthesis in general purpose programming languages.
POPL'23, 2023. [All Versions]. A new algorithm that synthesizes functional reactive programs from observation data, which iterates between a functional synthesis step, which attempts to generate a transition function over observed states, and an automata synthesis step, which adds any additional…
Nature Communications, 2022. [All Versions].
2023. [All Versions]. Rational meaning construction, a computational framework for language-informed thinking that combines neural language models with probabilistic models for rational inference. Linguistic meaning is framed as a context-sensitive mapping from natural language into a…
ICML'21, 2021. [All Versions]. Paper introducing the Latent Programmer, a two-level program synthesis method that first predicts a discrete latent code from input/output examples, and then generates the program in the target language.
ICML'23, 2023. [All Versions]. Paper presenting an approach that uses the LLM to read natural language problems and generate programs as the intermediate reasoning steps, but offloads the solution step to a runtime such as a Python interpreter. With PAL, decomposing the natural language problem…
ACL'23, 2023. [All Versions]. [NL2Code Website]. A paper presenting a comprehensive survey of 27 existing large language models for NL2Code, and also review benchmarks and metrics, suggesting that the key factors contributing to the success of large language models for NL2Code are “Large Size,…
ICSE'24, 2024. [All Versions]. A survey finding that developers are most motivated to use AI programming assistants because they help developers reduce key-strokes, finish programming tasks quickly, and recall syntax, but resonate less with using them to help brainstorm potential solutions.
2023. [All Versions]. A systematic literature review on LLM4SE, with a particular focus on understanding how LLMs can be exploited to optimize processes and outcomes.
Elsevier, 2008. [All Versions]. A pragmatical handbook for all kinds of knowledge representation modes.
Plato Stanford. A computational philosophy account on logic and ontology, mainly about the intersections of logic and ontology in many significant philosophy problems.
Plato Stanford. A computational philosophy account on the laugnage of though hypothesis, which proposes that thinking occurs in a mental language.
Plato Stanford.
Plato Stanford. A computational philosophy account on scientific representation, focusing on how scientific models represent their target systems.
Plato Stanford. A computational philosophy account on self-knowledge, which standardly refers to knowledge of one's own mental states—that is, of what one is feeling or thinking, or what one believes or desires.
Plato Stanford.
Plato Stanford.
Plato Stanford. A computational philosophy account on supervenience, where a set of properties A supervenes upon another set B just in case no two things can differ with respect to A-properties without also differing with respect to their B-properties.
Plato Stanford. A computational philosophy account on dialogical logic, which is a dialogue-based approach to logic and argumentation rooted in a research tradition that goes back to dialectics in Greek Antiquity, when problems were approached through dialogues in which opposing parties discussed…
Plato Stanford.
Plato Stanford. A computational philosophy account on Modal Logic, which is the study of the deductive behavior of the expressions 'it is necessary that' and 'it is possible that'.
Plato Stanford. A computational philosophy account on Epistemic Logic, which is a subfield of epistemology concerned with logical approaches to knowledge, belief and related notions.
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Knowledge Acquisition, 1993. [All Versions].
Physica D: Nonlinear Phenomena, 1990. [All Versions].
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hesreallyhim/awesome-claude-code
A hand-picked collection of the finest of resources for the most awesome of agents, Claude Code, the undisputed champion of coding companions, from the unstoppable team…
VoltAgent/awesome-agent-skills
A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.
josephmisiti/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
academic/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
analysis-tools-dev/static-analysis
⚙️ A curated list of static analysis (SAST) tools and linters for all programming languages, config files, build tools, and more. The focus is on tools which improve…