6 papers
TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text
Chengshuai Zhao, Pingchuan Ma, Dawei Li +4
The rapid development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously raising growing concerns about una…
Cornerstones or Stumbling Blocks? Deciphering the Rock Tokens in On-Policy Distillation
Yuxuan Jiang, Runchao Li, Shubhashis Roy Dipta +2
While recent work in Reinforcement Learning with Verifiable Rewards (RLVR) has shown that a small subset of critical tokens disproportionately drives reasoning gains, an analogous…
To See is Not to Learn: Protecting Multimodal Data from Unauthorized Fine-Tuning of Large Vision-Language Model
Chengshuai Zhao, Zhen Tan, Dawei Li +2
The rapid advancement of Large Vision-Language Models (LVLMs) is increasingly accompanied by unauthorized scraping and training on multimodal web data, posing severe copyright and…
The Quest for Efficient Reasoning: A Data-Centric Benchmark to CoT Distillation
Ruichen Zhang, Rana Muhammad Shahroz Khan, Zhen Tan +3
Data-centric distillation, including data augmentation, selection, and mixing, offers a promising path to creating smaller, more efficient student Large Language Models (LLMs) that…
Fairness in Multi-modal Medical Diagnosis with Demonstration Selection
Dawei Li, Zijian Gu, Peng Wang +6
Multimodal large language models (MLLMs) have shown strong potential for medical image reasoning, yet fairness across demographic groups remains a major concern. Existing debiasing…
Model Editing as a Double-Edged Sword: Steering Agent Ethical Behavior Toward Beneficence or Harm
Baixiang Huang, Zhen Tan, Haoran Wang +6
Agents based on Large Language Models (LLMs) have demonstrated strong capabilities across a wide range of tasks. However, deploying LLM-based agents in high-stakes domains comes wi…