AGI & CoCoSci
837 items from yuzheshi/awesome-agi-cocosci ★398
-
Semantic features of object concepts generated with GPT-3 escholarship.org
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…
-
Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI Capabilities escholarship.org
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…
-
Bridging cultural and cognitive perspectives on similarity reasoning escholarship.org
CogSci'22, 2022. [All Versions].
-
Bayesian Theory of Mind: Modeling Joint Belief-Desire Attribution escholarship.org
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…
-
One-shot learning of generative speech concepts escholarship.org
CogSci'14, 2014. [All Versions].
-
Preschoolers and adults make inferences from novel metaphors escholarship.org
CogSci'22, 2022. [All Versions]. A piece of evidence that understanding metaphors is capable for different cognitive development phases.
-
Modeling rules and similarity in colexification escholarship.org
CogSci'21, 2021. [All Versions]. Rule- and similarity-based generalization in colexification.
-
Learning Causal Schemata escholarship.org
CogSci'07, 2007, [[All Versions](https://scholar.google.com/scholar?
-
Theory of Mind en.wikipedia.org
Wikipedia. Wikipedia on Theory of Mind (ToM), a cognitive capability that estimating others' goal, belief, and desire.
-
Theory-theory en.wikipedia.org
Wikipedia. Wikipedia for the Theory theory, a perspective that contextualizes concepts in theoretical (or empirical) systems.
-
Situation Calculus en.wikipedia.org
Wikipedia. Wikipedia on Situation Calculus, a logic formalism designed for representing and reasoning about dynamical domains.
-
Metascience en.wikipedia.org
Wikipedia.
-
Insight en.wikipedia.org
Wikipedia. Wikipedia on insight.
-
Implicit Association Test en.wikipedia.org
Wikipedia. Wikipedia on the Implicit Association Test, a controversial assessment intended to detect subconscious associations between mental representations of objects (concepts) in memory.
-
Eureka Effect en.wikipedia.org
Wikipedia. Wikipedia on Eureka effect (a.k.a. Aha! moment, insight, and epiphany), the common human experience of suddenly understanding a previously incomprehensible problem or concept.
-
Epistemic Modal Logic en.wikipedia.org
Wikipedia.
-
Epiphany en.wikipedia.org
Wikipedia. Wikipedia on epiphany, the "feeling" when the Aha! moment comes.
-
Domain Engineering en.wikipedia.org
Wikipedia. Wikipedia encyclopedia entry on Domain Engineering.
-
Domain-Specific Language en.wikipedia.org
Wikipedia. Wikipedia encyclopedia entry on Domain Specific Languages.
-
Comparison of multi-paradigm programming languages en.wikipedia.org
Wikipedia. Programming languages may support multiple programming paradigms. This Wikipedia encyclopedia entry lists a concise reference for the programming paradigms.
-
Causality en.wikipedia.org
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…
-
Metabolic activity organizes olfactory representations elifesciences.org
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…
-
Robotic search for optimal cell culture in regenerative medicine elifesciences.org
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…
-
Value signals guide abstraction during learning elifesciences.org
eLife, 2022. [All Versions].
-
Foundations of intuitive power analyses in children and adults eccl.mit.edu
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…
-
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning dspace.mit.edu
Robotics: Science and Systems, 2018. [All Versions].
-
From understanding computation to understanding neural circuitry dspace.mit.edu
Neuroscience Research Program Bulletin, 1979. [All Versions].
-
Ten-month-old infants infer the value of goals from the costs of actions dspace.mit.edu
Science, 2017. [All Versions]. A piece of evidence for children's capability on ToM.
-
What is consciousness, and could machines have it? doi.org
Science, 2017. [All Versions]. A perspective on the two levels of consciousness in machine intelligence.
-
OpenLaw docs.openlaw.io
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…
-
Human Performance on Insight Problem Solving: A Review docs.lib.purdue.edu
The Journal of Problem Solving, 2011. [All Versions].
-
Meta-interpretive learning: application to grammatical inference doc.ic.ac.uk
Machine Learning, 2014. [All Versions]. Stephen Muggleton's original paper on Meta-Interpretive Learning (MIL).
-
Epigrams on programming dl.acm.org
ACM SIGPLAN Notices, 1982. [All Versions].
-
The Seven Tools of Causal Inference, with Reflections on Machine Learning dl.acm.org
Communications of the ACM, 2019. [All Versions]. Judea Pearl's review on causal inference in probabilistic graph models.
-
Apprenticeship Learning via Inverse Reinforcement Learning dl.acm.org
ICML'04, 2004. [All Versions]. Pieter Abbeel and Andrew Ng's original paper on inverse reinforcement learning (IRL).
-
Designing games with a purpose dl.acm.org
Communications of the ACM, 2008. [All Versions].
-
On the Effectiveness of Large Language Models in Domain-Specific Code Generation dl.acm.org
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…
-
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…
-
"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output dl.acm.org
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…
-
PhotoScout: Synthesis-Powered Multi-Modal Image Search dl.acm.org
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…
-
Building an Open Representation for Biological Protocols dl.acm.org
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…
-
Automatic curriculum learning for deep RL: a short survey dl.acm.org
IJCAI'20, 2020. [All Versions].
-
Finbert: A pre-trained financial language representation model for financial text mining dl.acm.org
IJCAI'20, 2020. [All Versions]. Predicting stock market trends, analyzing financial documents, and generating summaries of economic news articles, helping to disseminate financial knowledge.
-
Infinite Hidden Relational Models dl.acm.org
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…
-
Nonparametric Bayesian Logic dl.acm.org
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…
-
Bayesian Abductive Logic Programs: A Probabilistic Logic for Abductive Reasoning dl.acm.org
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…
-
What's the Game, then? Opportunities and Challenges for Runtime Behavior Generation dl.acm.org
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…
-
CoLadder: Manipulating Code Generation via Multi-Level Blocks dl.acm.org
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…
-
How Domain Experts Use an Embedded DSL dl.acm.org
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…
-
GarmentCode: Programming Parametric Sewing Patterns dl.acm.org
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…
- next page of items loading…
