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cs.CV2025
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 (…
cs.CV2024
μ-Bench: A Vision-Language Benchmark for Microscopy Understanding
Alejandro Lozano, Jeffrey Nirschl, James Burgess +4
Recent advances in microscopy have enabled the rapid generation of terabytes of image data in cell biology and biomedical research. Vision-language models (VLMs) offer a promising…
cs.CV2024
Revisiting Active Learning in the Era of Vision Foundation Models
Sanket Rajan Gupte, Josiah Aklilu, Jeffrey J. Nirschl +1
Foundation vision or vision-language models are trained on large unlabeled or noisy data and learn robust representations that can achieve impressive zero- or few-shot performance…