Publications
You can also find more about my research on Google Scholar profile.
(* indicate equal contribution)
Conference Papers (*Equal contribution)
Yiyang Zhou*, Chenhang Cui*, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao. Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR, 2024 & NeurIPS Workshop, 2023. pdf
Haoqin Tu*, Chenhang Cui*, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, Cihang Xie How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs. ECCV, 2024. pdf
Chenhang Cui, Yazhou Ren, Lifang He, et al A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective. NeurIPS, 2023. pdf
Chenhang Cui, Yazhou Ren, Lifang He, et al. Deep Multi-view Subspace Clustering with Anchor Graph. IJCAI, 2023. pdf
Jingyu Pu, Chenhang Cui, Xinyue Chen, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, S Yu Philip, Lifang He. Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering. AAAI, 2023. pdf
Zhaorun Chen, Yichao Du, Zichen Wen, Yiyang Zhou, Chenhang Cui, Zhenzhen Weng, Haoqin Tu, Chaoqi Wang, Zhengwei Tong, Qinglan Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge? ICML Workshop, 2024. pdf
Preprint
Chenhang Cui*, Yiyang Zhou*, Xiangyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao. Holistic Analysis of Hallucination in Large Vision-Language Models: Bias and Interference Challenges. pdf
Yiyang Zhou*, Chenhang Cui*, Rafael Rafailov, Chelsea Finn, Huaxiu Yao. Aligning Modalities in Vision Large Language Models via Preference Fine-tuning (ACL under review). pdf
Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao Calibrated self-rewarding vision language models pdf