3 papers
cs.AI2026
Personalization Meets Safety:Mechanisms,Risks,and Mitigations in Personalized LLMs
Yanyan Luo, Xue Han, Ruiqiao Bai +10
Large Language Models (LLMs) have enabled increasingly personalized interactions by adapting to users' preferences, contexts, and long-term histories. However, the mechanisms that…
cs.CL2026
Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation
Renfei Dang, Peng Hu, Zhejian Lai +3
Prior works have shown that fine-tuning on new knowledge can induce factual hallucinations in large language models (LLMs), leading to incorrect outputs when evaluated on previousl…
cs.CL2025
Large Language Models Are Cross-Lingual Knowledge-Free Reasoners
Peng Hu, Sizhe Liu, Changjiang Gao +5
Large Language Models have demonstrated impressive reasoning capabilities across multiple languages. However, the relationship between capabilities in different languages is less e…