collaborators

18 papers

cs.AI2026

TAPO: Tool-Aware Policy Optimization via Credit Transfer for Multimodal Search Agents

Chengqi Dong, Chuhuai Yue, Hang He +6

We identify and formally characterize credit misassignment as a systematic failure mode of GRPO in tool-augmented multimodal search agents: its uniform broadcast of trajectory-leve…

cs.CV2026

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training

Rongsheng Wang, Fenghe Tang, Zihang Jiang +10

Learning transferable and interpretable representations from medical volumetric scans remains challenging due to complex anatomical structures and weak, heterogeneous supervision p…

cs.CV2026

MMRad-22K: A Structured Multimodal Evidence Dataset for Chest X-ray Report Generation

Yichen Zhao, Zelin Peng, Fenghe Tang +3

Chest X-ray (CXR) reporting follows a region-based clinical workflow in which radiologists inspect anatomical regions and integrate localized findings into a final report. However,…

cs.CV2026

Training Multi-Image Vision Agents via End2End Reinforcement Learning

Chengqi Dong, Chuhuai Yue, Hang He +7

Recent VLM-based agents aim to replicate OpenAI O3's "thinking with images" via tool use, yet most open-source methods restrict inputs to a single image, limiting their applicabili…

cs.CV2026

Concept-to-Pixel: Prompt-Free Universal Medical Image Segmentation

Haoyun Chen, Fenghe Tang, Wenxin Ma +1

Universal medical image segmentation seeks to use a single foundational model to handle diverse tasks across multiple imaging modalities. However, existing approaches often rely he…

cs.CV2026

UCAD: Uncertainty-guided Contour-aware Displacement for semi-supervised medical image segmentation

Chengbo Ding, Fenghe Tang, Shaohua Kevin Zhou

Existing displacement strategies in semi-supervised segmentation only operate on rectangular regions, ignoring anatomical structures and resulting in boundary distortions and seman…