1 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
UltraVR: A Diagnostic Ultra-Resolution Image-VQA Benchmark for Evidence-Grounded Reasoning
Gexin Huang, Yanting Yang, Myeongkyun Kang +6
Vision-language models (VLMs) excel on visual question answering and multimodal reasoning benchmarks. Yet their capability on ultra-resolution images - where critical evidence is t…
Verification Mirage: Mapping the Reliability Boundary of Self-Verification in Medical VQA
Ruinan Jin, Beidi Zhao, Myeongkyun Kang +2
Self-verification, re-invoking the same vision language model (VLM) in a fresh context to check its own generated answer, is increasingly used as a default safety layer for medical…
Plug-and-Play Logit Fusion for Heterogeneous Pathology Foundation Models
Gexin Huang, Anqi Li, Yusheng Tan +4
Pathology foundation models (FMs) have become central to computational histopathology, offering strong transfer performance across a wide range of diagnostic and prognostic tasks.…
When RAG Hurts: Diagnosing and Mitigating Attention Distraction in Retrieval-Augmented LVLMs
Beidi Zhao, Wenlong Deng, Xinting Liao +4
While Retrieval-Augmented Generation (RAG) is one of the dominant paradigms for enhancing Large Vision-Language Models (LVLMs) on knowledge-based VQA tasks, recent work attributes…
PTCMIL: Multiple Instance Learning via Prompt Token Clustering for Whole Slide Image Analysis
Beidi Zhao, SangMook Kim, Hao Chen +4
Multiple Instance Learning (MIL) has advanced WSI analysis but struggles with the complexity and heterogeneity of WSIs. Existing MIL methods face challenges in aggregating diverse…