29 citations · 158 across the 26 of their papers we have counts for
5 papers · 1 filter
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
Yiyang Zhou, Chenhang Cui, Jaehong Yoon +5
Large vision-language models (LVLMs) have shown remarkable abilities in understanding visual information with human languages. However, LVLMs still suffer from object hallucination…
How Does Information Bottleneck Help Deep Learning?
Kenji Kawaguchi, Zhun Deng, Xu Ji +1
Numerous deep learning algorithms have been inspired by and understood via the notion of information bottleneck, where unnecessary information is (often implicitly) minimized while…
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks
Yuzhen Mao, Zhun Deng, Huaxiu Yao +3
As machine learning has been deployed ubiquitously across applications in modern data science, algorithmic fairness has become a great concern. Among them, imposing fairness constr…
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data
Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng +3
Language-supervised vision models have recently attracted great attention in computer vision. A common approach to build such models is to use contrastive learning on paired data a…
HappyMap: A Generalized Multi-calibration Method
Zhun Deng, Cynthia Dwork, Linjun Zhang
Multi-calibration is a powerful and evolving concept originating in the field of algorithmic fairness. For a predictor that estimates the outcome given covariates , and…