AGI & CoCoSci
837 items from yuzheshi/awesome-agi-cocosci ★398
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Abductive Knowledge Induction From Raw Data arxiv.org
IJCAI'21, 2021. [All Versions].
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Grounded Language Learning Fast and Slow arxiv.org
ICLR'21, 2021. [All Versions]. [Project].
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Compositional Generalization via Neural-Symbolic Stack Machines arxiv.org
NeurIPS'20, 2020. [All Versions].
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Neuro-Symbolic Visual Reasoning: Disentangling “Visual” from “Reasoning” arxiv.org
ICML'20, 2020. [All Versions].
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Noise or Signal: The Role of Backgrounds in Image Classification arxiv.org
ICLR'21, 2021. [All Versions]. [Code & Data]. [Project]. A perspective on image background provides strong clue for foreground classification.
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Analogy as Nonparametric Bayesian Inference over Relational Systems arxiv.org
CogSci'20, 2020. [All Versions].
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Learning programs by learning from failures arxiv.org
Machine Learning, 2020. [All Versions].
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PIQA: Reasoning about Physical Commonsense in Natural Language arxiv.org
AAAI'20, 2020. [All Versions].
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An Explicitly Relational Neural Network Architecture arxiv.org
ICML'20, 2020. [All Versions].
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ICLR'19, 2019. [All Versions].
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Neural Logic Machines arxiv.org
ICLR'19, 2019. [All Versions].
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Neural Logic Reinforcement Learning arxiv.org
ICML'19, 2019. [All Versions].
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Few-shot Bayesian imitation learning with logical program policies. arxiv.org
AAAI'20, 2020. [All Versions].
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Multi-Agent Cooperation and the Emergence of (Natural) Language arxiv.org
ICLR'17, 2017. [All Versions]. The original paper on the emergence of language in multi-agent reinforcement learning.
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ConceptNet 5.5: An Open Multilingual Graph of General Knowledge arxiv.org
AAAI'17, 2017. [All Versions]. Latest version of ConceptNet.
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Representation Learning: A Review and New Perspectives arxiv.org
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013. [All Versions]. Yoshua Bengio's review on representation learning.
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MoVer: Motion Verification for Motion Graphics Animations arxiv.org
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…
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The Scene Language: Representing Scenes with Programs, Words, and Embeddings arxiv.org
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…
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War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars arxiv.org
2023. [All Versions].
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The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4 arxiv.org
Microsoft Research AI4Science, 2023. [All Versions]. [Project]. A survey on the performance of LLMs within the context of scientific discovery, focusing on GPT-4.
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ChipNeMo: Domain-Adapted LLMs for Chip Design arxiv.org
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…
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Human Comprehensible Active Learning of Genome-Scale Metabolic Networks arxiv.org
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…
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Large Language Models for Software Engineering: A Systematic Literature Review arxiv.org
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.
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The SocialAI School: Insights from Developmental Psychology Towards Artificial Socio-Cultural Agents arxiv.org
ICML'23 Workshop on Theory-of-Mind, 2023. [All Versions]. [Project].
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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…
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SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks arxiv.org
NeurIPS'23, 2023. [All Versions]. [Project].
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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…
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CORWA: A Citation-Oriented Related Work Annotation Dataset arxiv.org
NAACL'22, 2022. [All Versions].
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A Grammar of Hypotheses for Visualization, Data, and Analysis arxiv.org
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…
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The Quest for a Common Model of the Intelligent Decision Maker arxiv.org
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.
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Learning to Act and Observe in Partially Observable Domains arxiv.org
2021. [All Versions].
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Program Synthesis with Large Language Models arxiv.org
2021. [All Versions]. This paper explores the limits of the current generation of large language models for program synthesis in general purpose programming languages.
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Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability arxiv.org
NeurIPS'21, 2021. [All Versions]. A formal treatment on the generalization problem in reinforcement learning.
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Automated Biodesign Engineering by Abductive Meta-Interpretive Learning arxiv.org
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…
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Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning arxiv.org
ICLR'21, 2021. [All Versions].
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ICML'21, 2021. [All Versions].
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Exploring Urban Form Through Openstreetmap Data: A Visual Introduction arxiv.org
Urban Experience and Design: Contemporary Perspectives on Improving the Public Realm, 2020. [All Versions]. [OSMnx Tool]. [OpenStreetMap Website].
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Inductive logic programming at 30: a new introduction arxiv.org
Journal of Artificial Intelligence Research, 2020. [All Versions]. A 30-year comprehensive review on Inductive Logic Programming.
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Learning Task-General Representations with Generative Neuro-Symbolic Modeling arxiv.org
ICLR'21, 2021. [All Versions].
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Discovering Symbolic Models from Deep Learning with Inductive Biases arxiv.org
NeurIPS'20, 2020. [All Versions].
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ICML'20, 2020. [All Versions].
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Compositionality and Generalization in Emergent Languages arxiv.org
ACL'20, 2020. [All Versions].
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Generating new concepts with hybrid neuro-symbolic models. arxiv.org
CogSci'20, 2020. [All Versions].
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3D dynamic scene graphs: Actionable spatial perception with places, objects, and humans arxiv.org
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…
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X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust arxiv.org
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…
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From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following arxiv.org
ICLR'19, 2019. [All Versions].
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Learning to Make Analogies by Contrasting Abstract Relational Structure arxiv.org
ICLR'19, 2019. [All Versions].
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Human few-shot learning of compositional instructions arxiv.org
CogSci'19, 2019. [All Versions].
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A Tutorial on Bayesian Optimization arxiv.org
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…
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DeepProbLog: Neural Probabilistic Logic Programming arxiv.org
NeurIPS'18, 2018. [All Versions]. The original paper on neuro-symbolic probabilistic programming.
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