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awesome-theory-of-mind

github.com/mars-tin/awesome-theory-of-mind ↗

Machine Theory of Mind Reading List. Built upon EMNLP Findings 2023 Paper: Towards A Holistic Landscape of Situated Theory of Mind in Large Language Models

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Overview1. ToM Community Resources2. Machine ToM Surveys and Position Papers3. Cognitive Underpinnings of ToM4. Computational Inquiry to ToM in Foundation Models4. ToM Benchmarks and Platforms5. Computational Modeling of ToM6. ToM Application

Use this list with your AI agent

Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:

"Show me 3.1 definition and importance of tom in human cognition (selected) resources from awesome-theory-of-mind"

Installation instructions →

What's inside

3. Cognitive Underpinnings of ToM

  • [Book]3.1 Definition and Importance of ToM in Human Cognition (Selected)

  • [Paper]3.1 Definition and Importance of ToM in Human Cognition (Selected)

  • [Paper]3.2 Taxonomies of ToM and Mental States

  • [Paper]3.1 Definition and Importance of ToM in Human Cognition (Selected)

  • [Paper]3.1 Definition and Importance of ToM in Human Cognition (Selected)

  • [Paper]3.1 Definition and Importance of ToM in Human Cognition (Selected)

Overview

6. ToM Application

  • [Paper]6.7 Privacy

  • [Paper]6.6 Healthcare

  • [Paper]6.1 Pragmatics and Instruction Generation/Following

  • [Paper]6.1 Pragmatics and Instruction Generation/Following

  • [Paper]6.2 Dialogue Processing and Generation

  • [Paper]6.1 Pragmatics and Instruction Generation/Following

1. ToM Community Resources

2. Machine ToM Surveys and Position Papers

4. Computational Inquiry to ToM in Foundation Models

  • [Paper]4.1 Probing Intrinsic Mental States

  • [Paper]4.1 Probing Intrinsic Mental States

  • [Paper]4.1 Probing Intrinsic Mental States

  • [Paper]4.1 Evidence for Understanding Extrinsic Mental States

  • [Paper]4.1 Evidence for Understanding Extrinsic Mental States

  • [Paper]4.1 Evidence for Understanding Extrinsic Mental States

5. Computational Modeling of ToM

  • [Paper]5.4 Bayesian and (Inverse) Reinforcement Learning Based ToM Modeling

  • [Paper]5.1 Learning Latent Representation for ToM

  • [Paper]5.1 Learning Latent Representation for ToM

  • [Paper]5.1 Learning Latent Representation for ToM

  • [Paper]5.1 Learning Latent Representation for ToM

  • [Paper]5.2 Learning (Neural-)Symbolic Representation for ToM

4. ToM Benchmarks and Platforms

Showing a sample of 92 resources. View the full list on GitHub →