29 citations · 49 across the 12 of their papers we have counts for
5 papers · 1 filter
Reliable and Responsible Foundation Models: A Comprehensive Survey
Xinyu Yang, Junlin Han, Rishi Bommasani +49
Foundation models, including Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Image Generative Models (i.e, Text-to-Image Models and Image-Editing Models), a…
Calibrated Self-Rewarding Vision Language Models
Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng +7
Large Vision-Language Models (LVLMs) have made substantial progress by integrating pre-trained large language models (LLMs) and vision models through instruction tuning. Despite th…
Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
Yiyang Zhou, Chenhang Cui, Rafael Rafailov +2
Instruction-following Vision Large Language Models (VLLMs) have achieved significant progress recently on a variety of tasks. These approaches merge strong pre-trained vision model…
Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges
Chenhang Cui, Yiyang Zhou, Xinyu Yang +4
While GPT-4V(ision) impressively models both visual and textual information simultaneously, it's hallucination behavior has not been systematically assessed. To bridge this gap, we…
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…