Author

Soyoung Oh

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#artificial intelligence Preprint Oct 2026

Learning Perception to Action Rules through Reinforcement Learning for Theory-of-Mind Reasoning

This work generates concise rules that express relations between perception to action and uses Group Relative Policy Optimization (GRPO) to train Qwen2.5 and Llama3 models across four ToM benchmarks, suggesting that explicit rules help models bridge the reasoning gap in ToM and support knowledge transfer across models.

Soyoung Oh, Nursulu Sagimbayeva, N. Jennings et al. · 0 citations

#artificial intelligence Jun 2026

A retrieval conditioned rebinding circuit for dynamic entity tracking in large language models

The results reveal an interpretable mechanism for context dependent state tracking in LLMs, a retrieval conditioned rebinding mechanism, a compact attention head circuit that propagated binding information and when the entity is queried, uses the updated binding to retrieve the corresponding attribute.

Soyoung Oh, Vera Demberg · arXiv.org · 3 citations