3 citations · 3 across the 14 of their papers we have counts for
4 papers · 1 filter
Mitigating Hallucinations in Large Language Models via Causal Reasoning
Yuangang Li, Yiqing Shen, Yi Nian +7
Large language models (LLMs) exhibit logically inconsistent hallucinations that appear coherent yet violate reasoning principles, with recent research suggesting an inverse relatio…
Don't Let It Hallucinate: Premise Verification via Retrieval-Augmented Logical Reasoning
Yuehan Qin, Shawn Li, Yi Nian +3
Large language models (LLMs) have shown substantial capacity for generating fluent, contextually appropriate responses. However, they can produce hallucinated outputs, especially w…
JailDAM: Jailbreak Detection with Adaptive Memory for Vision-Language Model
Yi Nian, Shenzhe Zhu, Yuehan Qin +4
Multimodal large language models (MLLMs) excel in vision-language tasks but also pose significant risks of generating harmful content, particularly through jailbreak attacks. Jailb…
Secure On-Device Video OOD Detection Without Backpropagation
Shawn Li, Peilin Cai, Yuxiao Zhou +7
Out-of-Distribution (OOD) detection is critical for ensuring the reliability of machine learning models in safety-critical applications such as autonomous driving and medical diagn…