CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models
Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demonstrate promising performance on standard ToM benchmarks, we observe that they often fail to generalize to complex task-specific scenarios, relying heavily on prompt scaffolding to mimic reasoning. The critical misalignment between the internal knowledge and external behavior raises a fundamental question: Do LLMs truly possess intrinsic cognition, and can they externalize this internal knowledge into stable, high-quality behaviors? To answer this, we introduce CoSToM (Causal-oriented Steering for ToM alignment), a framework that transitions ...
| Authors | Mengfan Li, Xuanhua Shi, Yang Deng |
|---|---|
| Primary category | cs.CL |
| Published | 11 April 2026 |
| Last updated at source | 11 April 2026 |
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