45 citations · 204 across the 37 of their papers we have counts for
5 papers · 1 filter
The Instinctive Bias: Spurious Images lead to Illusion in MLLMs
Tianyang Han, Qing Lian, Rui Pan +5
Large language models (LLMs) have recently experienced remarkable progress, where the advent of multi-modal large language models (MLLMs) has endowed LLMs with visual capabilities,…
DetGPT: Detect What You Need via Reasoning
Renjie Pi, Jiahui Gao, Shizhe Diao +8
In recent years, the field of computer vision has seen significant advancements thanks to the development of large language models (LLMs). These models have enabled more effective…
Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts
Zhihong Chen, Shizhe Diao, Benyou Wang +2
Medical vision-and-language pre-training (Med-VLP) has shown promising improvements on many downstream medical tasks owing to its applicability to extracting generic representation…
Write and Paint: Generative Vision-Language Models are Unified Modal Learners
Shizhe Diao, Wangchunshu Zhou, Xinsong Zhang +1
Recent advances in vision-language pre-training have pushed the state-of-the-art on various vision-language tasks, making machines more capable of multi-modal writing (image-to-tex…
VLUE: A Multi-Task Benchmark for Evaluating Vision-Language Models
Wangchunshu Zhou, Yan Zeng, Shizhe Diao +1
Recent advances in vision-language pre-training (VLP) have demonstrated impressive performance in a range of vision-language (VL) tasks. However, there exist several challenges for…