collaborators

12 papers

cs.CV2026

SalArt-VQA: Diagnosing Whether VLMs Understand Salient Artifacts in Generated Images

Xiaoxiao Sun, Ruotian Zhang, Junzhe Huang +2

Vision-language models (VLMs) are increasingly used to detect whether AI-generated images contain visible artifacts, yet their ability to analyze such artifacts remains poorly unde…

cs.CV2026

MMBU: A Massive Multi-modal Biomedical Understanding Benchmark to Probe the Perception Capabilities of Vision-Language Models

Ryan D'Cunha, Alejandro Lozano, Xiaoxiao Sun +17

Vision and language models (VLMs) hold immense promise to transform biomedical imaging workflows, from detecting lesions in chest X-rays to profiling cellular features in microscop…

cs.LG2026

PaperSearchQA: Learning to Search and Reason over Scientific Papers with RLVR

James Burgess, Jan N. Hansen, Duo Peng +5

Search agents are language models (LMs) that reason and search knowledge bases (or the web) to answer questions; recent methods supervise only the final answer accuracy using reinf…

cs.CV2025

The Impact of Image Resolution on Biomedical Multimodal Large Language Models

Liangyu Chen, James Burgess, Jeffrey J Nirschl +2

Imaging technologies are fundamental to biomedical research and modern medicine, requiring analysis of high-resolution images across various modalities. While multimodal large lang…

cs.CV2025

No Tokens Wasted: Leveraging Long Context in Biomedical Vision-Language Models

Min Woo Sun, Alejandro Lozano, Javier Gamazo Tejero +8

Embedding vision-language models (VLMs) are typically pretrained with short text windows (<77 tokens), which forces the truncation of long-format captions. Yet, the distribution of…

q-bio.QM2025

CellFlux: Simulating Cellular Morphology Changes via Flow Matching

Yuhui Zhang, Yuchang Su, Chenyu Wang +8

Building a virtual cell capable of accurately simulating cellular behaviors in silico has long been a dream in computational biology. We introduce CellFlux, an image-generative mod…