7 papers · 1 filter
Topo-R1: Detecting Topological Anomalies via Vision-Language Models
Meilong Xu, Qingqiao Hu, Xiaoling Hu +6
Topology is critical in tubular structures such as blood vessels, nerve fibers, and road networks, where connectivity and loop structure govern downstream functional analysis. Visi…
LoC-Path: Learning to Compress for Pathology Multimodal Large Language Models
Qingqiao Hu, Weimin Lyu, Meilong Xu +5
Whole Slide Image (WSI) MLLMs are difficult to build and deploy because gigapixel slides induce thousands of visual tokens, while only a small fraction of regions is diagnostically…
RB-FT: Rationale-Bootstrapped Fine-Tuning for Video Classification
Meilong Xu, Di Fu, Jiaxing Zhang +7
Vision Language Models (VLMs) are becoming increasingly integral to multimedia understanding; however, they often struggle with domain-specific video classification tasks, particul…
Towards Better Optimization For Listwise Preference in Diffusion Models
Jiamu Bai, Xin Yu, Meilong Xu +6
Reinforcement learning from human feedback (RLHF) has proven effectiveness for aligning text-to-image (T2I) diffusion models with human preferences. Although Direct Preference Opti…
MATCH: Multi-faceted Adaptive Topo-Consistency for Semi-Supervised Histopathology Segmentation
Meilong Xu, Xiaoling Hu, Shahira Abousamra +2
In semi-supervised segmentation, capturing meaningful semantic structures from unlabeled data is essential. This is particularly challenging in histopathology image analysis, where…
Multi-Channel Uncertainty-Weighted Score Matching for Conditional Diffusion in Medical UDA
Chen Li, Meilong Xu, Xiaoling Hu +2
Robust medical image segmentation across modalities remains challenging due to severe domain shifts and the lack of target-domain labels. While diffusion models have been explored…
Spatial Diffusion for Cell Layout Generation
Chen Li, Xiaoling Hu, Shahira Abousamra +2
Generative models, such as GANs and diffusion models, have been used to augment training sets and boost performances in different tasks. We focus on generative models for cell dete…