Decomposing Theory of Mind: How Emotional Processing Mediates ToM Abilities in LLMs

November 19, 2025 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Ivan Chulo, Ananya Joshi arXiv ID 2511.15895 Category cs.AI: Artificial Intelligence Citations 0 Venue arXiv.org Last Checked 4 months ago
Abstract
Recent work shows activation steering substantially improves language models' Theory of Mind (ToM) (Bortoletto et al. 2024), yet the mechanisms of what changes occur internally that leads to different outputs remains unclear. We propose decomposing ToM in LLMs by comparing steered versus baseline LLMs' activations using linear probes trained on 45 cognitive actions. We applied Contrastive Activation Addition (CAA) steering to Gemma-3-4B and evaluated it on 1,000 BigToM forward belief scenarios (Gandhi et al. 2023), we find improved performance on belief attribution tasks (32.5\% to 46.7\% accuracy) is mediated by activations processing emotional content : emotion perception (+2.23), emotion valuing (+2.20), while suppressing analytical processes: questioning (-0.78), convergent thinking (-1.59). This suggests that successful ToM abilities in LLMs are mediated by emotional understanding, not analytical reasoning.
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