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cs.CL2026

Can Released LLM Vocabularies Support Token-Level Estimation of Hidden Corpora?

Qingjie Zhang, Xingzhang Ren, Zixuan Chen +6

Pretraining corpus composition shapes LLM capabilities, but it often remains hidden even when model weights are released. Prior work has inferred corpus mixtures or traced specific…

cs.CL2026

Auditing Chinese Web-scale Corpora via Sampled BPE Token Statistics

Qingjie Zhang, Ziqi Tang, Jie Zhang +7

Chinese web pollution has surfaced in LLMs, motivating audits of upstream Chinese corpora. However, auditing such corpora faces three challenges: (1) their web-scale size makes ful…

cs.CL2026

ConsisGuard: Aligning Safety Deliberation with Policy Enforcement in LLM Guardrails

Yan Wang, Zhixuan Chu, Zihao Xue +9

Reasoning-based LLM guardrails improve safety moderation by generating explicit rationales before issuing final decisions. However, their rationales do not always lead to faithful…

cs.CL2026

How LoRA Remembers? A Parametric Memory Law for LLM Finetuning

Ziwen Xu, Haiwen Hong, Linsong Yu +4

Large Language Models (LLMs) must continuously learn and update knowledge to remain effective in dynamic real-world environments. While Low-Rank Adaptation (LoRA) is widely used fo…

cs.CL2025

AIR: A Systematic Analysis of Annotations, Instructions, and Response Pairs in Preference Dataset

Bingxiang He, Wenbin Zhang, Jiaxi Song +11

Preference learning is critical for aligning large language models (LLMs) with human values, yet its success hinges on high-quality datasets comprising three core components: Prefe…