Language Models Might Not Understand You: Evaluating Theory of Mind via Story Prompting
cs.CL, cs.AI
Submitted: 2025-06-23
Updated: 2026-09-01
Code: https://github.com/ngetachew/StorySim
Terminology
Sources
- GPT-4 Technical Report
- On the Diversity of Synthetic Data and its Impact on Training Large Language Models
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models
- GPT-4o System Card
- OpenAI o1 System Card
- Evaluating Large Language Models in Theory of Mind Tasks
- Do Large Language Models Have a Planning Theory of Mind? Evidence from MindGames: a Multi-Step Persuasion Task
- PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models
- Explore Theory of Mind: Program-guided adversarial data generation for theory of mind reasoning
- Does Synthetic Data Generation of LLMs Help Clinical Text Mining?
- Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks
- MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining
- Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning
- Qwen3 Technical Report
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