3 papers
cs.CV2026
SciVQR: A Multidisciplinary Multimodal Benchmark for Advanced Scientific Reasoning Evaluation
Longteng Guo, Xuanxu Lin, Dongze Hao +5
Scientific reasoning is a key aspect of human intelligence, requiring the integration of multimodal inputs, domain expertise, and multi-step inference across various subjects. Exis…
cs.CV2026
S1-MMAlign: A Large-Scale, Multi-Disciplinary Dataset for Scientific Figure-Text Understanding
He Wang, Longteng Guo, Pengkang Huo +4
Multimodal learning has revolutionized general domain tasks, yet its application in scientific discovery is hindered by the profound semantic gap between complex scientific imagery…
cs.CV2026
M-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering
Jiatong Ma, Longteng Guo, Yuchen Liu +4
We present M-VQA, a novel knowledge-based Visual Question Answering (VQA) benchmark, to enhance the evaluation of multimodal large language models (MLLMs) in fine-grained multi…