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  1. Home
  2. /Repositories
  3. /sileod/llm-theory-of-mind
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

sileod/llm-theory-of-mind

Testing Theory of Mind (ToM) in language models with epistemic logic

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 49%From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond →
  • PossiblePossibly related (embedding) · 49%Grounding LLM Reasoning under Incomplete Graph Evidence →
  • PossiblePossibly related (embedding) · 49%The Riddle Riddle: Testing Flexible Reasoning in Large Language Models and Humans →
  • PossiblePossibly related (embedding) · 48%Knowledge Distillation of Black-Box Large Language Models →
  • PossiblePossibly related (embedding) · 48%Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action →
  • PossiblePossibly related (embedding) · 46%Knowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMs →
  • PossiblePossibly related (embedding) · 47%Validity of LLMs as data annotators: AMALIA on authority →
  • PossiblePossibly related (embedding) · 46%Production and Perception in LLMs: A Token Probability Approach →

Implements

paperFrom Tokens to States: LLMs as a Special Case of World Models and the Continuous Path BeyondpaperGrounding LLM Reasoning under Incomplete Graph EvidencepaperThe Riddle Riddle: Testing Flexible Reasoning in Large Language Models and HumanspaperTheory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action

Covers

newsKnowledge Distillation of Black-Box Large Language Models

Implements (incoming)

paperKnowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMspaperValidity of LLMs as data annotators: AMALIA on authoritypaperProduction and Perception in LLMs: A Token Probability ApproachpaperKnowledgeless Language Models: Suppressing Parametric Recall for Evidence-Grounded Language Modeling

Related across the graph

paperProduction and Perception in LLMs: A Token Probability ApproachnewsKnowledge Distillation of Black-Box Large Language ModelspaperKnowledgeless Language Models: Suppressing Parametric Recall for Evidence-Grounded Language ModelingpaperGrounding LLM Reasoning under Incomplete Graph EvidencepaperValidity of LLMs as data annotators: AMALIA on authoritypaperKnowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMspaperTheory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and ActionpaperThe Riddle Riddle: Testing Flexible Reasoning in Large Language Models and HumanspaperFrom Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond
Knowledge path·PProduction and Perception in LLMs: A Token Probability Approach→NKnowledge Distillation of Black-Box Large Language Models→PKnowledgeless Language Models: Suppressing Parametric Recall for Evidence-Grounded Language Modeling→Rsileod/llm-theory-of-mind

Topics

chatgptdatasetenglishepistemic-logicepistemic-reasoninggpt-4language-modelllmmodal-logicmuddy-children

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Graph trust82Primary
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