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cs.CV2026
Input- and Feature-Space Correction for Cross-Hospital IHC Grading
Jongwoon Lee, Jhair Gallardo, Christopher Kanan
Pathology foundation models (FMs) are trained predominantly on hematoxylin and eosin (H&E) images but are increasingly used as frozen feature extractors for immunohistochemistry (I…
cs.CV2026
Unlocking ImageNet's Multi-Object Nature: Automated Large-Scale Multilabel Annotation
Junyu Chen, Md Yousuf Harun, Christopher Kanan
The original ImageNet benchmark enforces a single-label assumption, despite many images depicting multiple objects. This leads to label noise and limits the richness of the learnin…
cs.CV2023
BloomVQA: Assessing Hierarchical Multi-modal Comprehension
Yunye Gong, Robik Shrestha, Jared Claypoole +4
We propose a novel VQA dataset, BloomVQA, to facilitate comprehensive evaluation of large vision-language models on comprehension tasks. Unlike current benchmarks that often focus…