README.md

metadata

license: apache-2.0
task_categories:
  - text-classification
language:
  - en
task_ids:
  - natural-language-inference
  - multi-input-text-classification
multilinguality:
  - monolingual
tags:
  - theory of mind
  - tom
  - Logical-Reasoning
  - Modal-Logic
  - Reasoning
  - Logics
  - Logic
  - nli
  - model-checking
  - natural language inference
dataset_info:
  features:
    - name: premise
      dtype: string
    - name: smcdel_problem
      dtype: string
    - name: n_announcements
      dtype: int64
    - name: pbcheck
      dtype: string
    - name: hypothesis
      dtype: string
    - name: setup
      dtype: string
    - name: hypothesis_depth
      dtype: int64
    - name: n_agents
      dtype: int64
    - name: label
      dtype: int64
    - name: names
      sequence: string
    - name: index
      dtype: int64
    - name: s-l
      dtype: string
    - name: deberta_pred
      dtype: int64
    - name: deberta_confidence
      dtype: float64
    - name: difficulty
      dtype: float64
  splits:
    - name: train
      num_bytes: 8619563.842139175
      num_examples: 11174
    - name: validation
      num_bytes: 2873445.0789304124
      num_examples: 3725
    - name: test
      num_bytes: 2873445.0789304124
      num_examples: 3725
  download_size: 2991434
  dataset_size: 14366454

Mindgame dataset

Code: https://github.com/sileod/llm-theory-of-mind

Article (Accepted at EMNLP 2023 Findings): https://arxiv.org/abs/2305.03353

@article{sileo2023mindgames,
  title={MindGames: Targeting Theory of Mind in Large Language Models with Dynamic Epistemic Modal Logic},
  author={Sileo, Damien and Lernould, Antoine},
  journal={arXiv preprint arXiv:2305.03353},
  year={2023}
}