2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific Research
James Burgess, Jeffrey J Nirschl, Laura Bravo-Sánchez +20
Scientific research demands sophisticated reasoning over multimodal data, a challenge especially prevalent in biology. Despite recent advances in multimodal large language models (…
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation
Yuhui Zhang, Yuchang Su, Yiming Liu +9
The rapid development of vision language models (VLMs) demands rigorous and reliable evaluation. However, current visual question answering (VQA) benchmarks often depend on open-en…
Multimodal Generalized Category Discovery
Yuchang Su, Renping Zhou, Siyu Huang +4
Generalized Category Discovery (GCD) aims to classify inputs into both known and novel categories, a task crucial for open-world scientific discoveries. However, current GCD method…
Why are Visually-Grounded Language Models Bad at Image Classification?
Yuhui Zhang, Alyssa Unell, Xiaohan Wang +4
Image classification is one of the most fundamental capabilities of machine vision intelligence. In this work, we revisit the image classification task using visually-grounded lang…