Papers with PathoHR-Bench

1 papers
PathoHR: Hierarchical Reasoning for Vision-Language Models in Pathology (2025.findings-emnlp)

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Challenge: Current vision-language (VL) models fail to capture complex reasoning required for interpreting structured pathological reports.
Approach: They propose a pathology-specific VL training scheme that generates enhanced and perturbed samples for multimodal contrastive learning.
Outcome: The proposed approach achieves state-of-the-art performance on PathoHR-Bench and six additional pathology datasets, highlighting its effectiveness in fine-grained pathology representation.

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