Author

Zixuan Wang

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#artificial intelligence Preprint Sep 2026

Mitigating LLM Over-Refusal via Dynamic Semantic Routing Calibration

Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior studies primarily attribute this to static representation overlap, largely overlooking the underlying dynamic mechanisms. In this paper, we present the mechanistic analysis...

Zi-Xuan Wang, Bing-Jie Zhang, He Zhao et al. · 0 citations

Preprint Aug 2026

Learning What to Remember: Test-Time Training via Context Distillation

This work proposes TTCD, a TTT framework that introduces a self-supervised objective for allocating limited memory capacity for future use, and focuses on an in-place variant: In-Place TTCD, which uses the existing MLP parameters as the fast weights.

Zi-Xuan Wang, Xingyu Dang, Ruiming Zhu et al. · 0 citations