3 papers
cs.CV2026
Do Pathology Vision-Language Models Truly See Pathology?
Chengyang Zhang, Wenchuan Zhang, Bo Li +10
Pathology vision-language models (VLMs) have recently progressed rapidly and are commonly evaluated by answer accuracy on pathology VQA benchmarks. However, we dig into current eva…
cs.AI2026
PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow
Chengyang Zhang, Wenchuan Zhang, Bo Li +5
Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patch-level reasoning remains ch…
cs.AI2024
Validation of the Practicability of Logical Assessment Formula for Evaluations with Inaccurate Ground-Truth Labels: An Application Study on Tumour Segmentation for Breast Cancer
Yongquan Yang, Hong Bu
The logical assessment formula (LAF) is a new theory proposed for evaluations with inaccurate ground-truth labels (IAGTLs) to assess the predictive models for artificial intelligen…