6 papers
Cascade: Hierarchical Recoverability Control for Large Language Model Unlearning
Qingchen Yu, Shiying Duan, Xiaodong Li +5
Large Language Model (LLM) unlearning is essential for removing sensitive or copyrighted knowledge while preserving general utility. Existing methods often leave residual knowledge…
A Hyperbolicity Atlas of Large Language Model Hidden States
Zhichao Yang, Yuanze Hu, Gen Li +7
LLM hidden states are ordinary vectors, but the distances among those vectors may still show hierarchical structure. To our knowledge, this paper is the first systematic study of w…
PACT: Learning Diverse Diagnostic Strategies via Privileged Synthesis and Branch Consensus
Gen Li, Yuanze Hu, Zhichao Yang +10
Clinical diagnosis requires flexible use of multiple reasoning paradigms under incomplete patient information. Existing LLM-based medical agents show strong medical reasoning abili…
State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading
Yuanze Hu, Gen Li, Yuqin Lan +5
Multimodal large language models (MLLMs) have achieved impressive progress on general multimodal tasks, yet they remain brittle on dial-based measurement reading. In this paper, we…
Mask-Free Privacy Extraction and Rewriting: A Domain-Aware Approach via Prototype Learning
Xiaodong Li, Yuhua Wang, Qingchen Yu +5
Client-side privacy rewriting is crucial for deploying LLMs in privacy-sensitive domains. However, existing approaches struggle to balance privacy and utility. Full-text methods of…
The Achilles' Heel of LLMs: How Altering a Handful of Neurons Can Cripple Language Abilities
Zixuan Qin, Qingchen Yu, Kunlin Lyu +2
Large Language Models (LLMs) have become foundational tools in natural language processing, powering a wide range of applications and research. Many studies have shown that LLMs sh…