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Wen-Zhi Fang

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#machine learning Preprint Sep 2026

Theory of Scene: Breaking the Symmetry Trap in Multi-Agent LLM Coordination

Tory of Scene (ToS), a training-free reasoning schema in which each agent reads its public role, the only difference between the agents, and the task context they all observe, is proposed, which outperforms all six baselines on every benchmark, and each baseline falls far behind it in at least one setting.

Liang-Qi Yuan, Wen-Zhi Fang, Shi-Qiang Wang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Reasoning-Preserving Fine-Tuning of Post-RL LLMs with Null-Basis LoRA

Reinforcement learning (RL)-based post-training has become an effective approach for eliciting reasoning capabilities in large language models (LLMs). However, adapting post-RL models to new knowledge domains or behaviors through subsequent supervised fine-tuning (SFT) can severely overwrite these capabilities. Existin...

Wen-Zhi Fang, Nicholas Tzou, L. Valkov et al. · 0 citations

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