MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific Research.

ABSTRACT: Scientific research demands sophisticated reasoning over multimodal data, a challenge especially prevalent in biology. Despite recent advances in multimodal large language models (MLLMs) for AI-assisted research, existing multimodal reasoning benchmarks only target up to college-level difficulty, while research-level benchmarks emphasize lower-level perception, falling short of the complex multimodal reasoning needed for scientific discovery. To bridge this gap, we introduce MicroVQA, a visual-question answering (VQA) benchmark designed to assess three reasoning capabilities vital in research workflows: expert image understanding, hypothesis generation, and experiment proposal. MicroVQA consists of 1,042 multiple-choice questions (MCQs) curated by biology experts across diverse microscopy

SUBMITTER: Burgess J 

PROVIDER: S-EPMC11957224 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature