Author

Shengfang Zhai

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#natural language process... Preprint Sep 2026

Membership Inference in Fine-tuned Diffusion Language Models via Token-level Memorization Asymmetry

This work identifies a phenomenon termed token-level memorization asymmetry through theoretical analysis of diffusion training dynamics and proposes Q-Skew, a quantile-weighted skewness-based indicator for membership inference on finetuned DLMs.

Sheng-Fang Zhai, Leo Marchyok, Yu-Ling Shi et al. · 1 citation · ⚡1

Preprint Aug 2026

Don't Solve, Just Compare: Tiny Advisors for Runtime Intervention in LLM Agents

Comparison-Only Tiny Advisor (COTA), a comparison-only framework for constructive runtime intervention that shows that constructive runtime intervention can remain effective even when the auxiliary model has substantially weaker task-solving capability than the actor.

Yan-Ze Jiang, Mingxuan Li, Yuhao Wang et al. · 2 citations