10 citations · 26 across the 15 of their papers we have counts for
16 papers
MotionMERGE: A Multi-granular Framework for Human Motion Editing, Reasoning, Generation, and Explanation
Bizhu Wu, Jinheng Xie, Wenting Chen +5
Recent motion-language models unify tasks like comprehension and generation but operate at a coarse granularity, lacking fine-grained understanding and nuanced control over body pa…
MMedExpert-R1: Strengthening Multimodal Medical Reasoning via Domain-Specific Adaptation and Clinical Guideline Reinforcement
Meidan Ding, Jipeng Zhang, Wenxuan Wang +4
Medical Vision-Language Models (MedVLMs) excel at perception tasks but struggle with complex clinical reasoning required in real-world scenarios. While reinforcement learning (RL)…
Benchmarking Egocentric Clinical Intent Understanding Capability for Medical Multimodal Large Language Models
Shaonan Liu, Guo Yu, Xiaoling Luo +4
Medical Multimodal Large Language Models (Med-MLLMs) require egocentric clinical intent understanding for real-world deployment, yet existing benchmarks fail to evaluate this criti…
SurvAgent: Hierarchical CoT-Enhanced Case Banking and Dichotomy-Based Multi-Agent System for Multimodal Survival Prediction
Guolin Huang, Wenting Chen, Jiaqi Yang +5
Survival analysis is critical for cancer prognosis and treatment planning, yet existing methods lack the transparency essential for clinical adoption. While recent pathology agents…
Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models
Wenting Chen, Guo Yu, Yiu-Fai Cheung +5
Large language models (LLMs) show significant potential in healthcare, prompting numerous benchmarks to evaluate their capabilities. However, concerns persist regarding the reliabi…
FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs
Xiaoqin Wang, Xusen Ma, Xianxu Hou +6
Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in various tasks. However, effectively evaluating these MLLMs on face perception remains largely…