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cs.CL2025
Towards Long Context Hallucination Detection
Siyi Liu, Kishaloy Halder, Zheng Qi +6
Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. However, they are prone to contextual hallucination, generating information that is eith…
cs.CL2024
Rethinking LLM Uncertainty: A Multi-Agent Approach to Estimating Black-Box Model Uncertainty
Yu Feng, Phu Mon Htut, Zheng Qi +7
Quantifying uncertainty in black-box LLMs is vital for reliable responses and scalable oversight. Existing methods, which gauge a model's uncertainty through evaluating self-consis…
cs.CL2024
Unraveling and Mitigating Safety Alignment Degradation of Vision-Language Models
Qin Liu, Chao Shang, Ling Liu +7
The safety alignment ability of Vision-Language Models (VLMs) is prone to be degraded by the integration of the vision module compared to its LLM backbone. We investigate this phen…