1 citations · 1 across the 5 of their papers we have counts for
5 papers
MIRL: Mutual Information-Guided Reinforcement Learning for Vision-Language Models
Yin Zhang, Jiaxuan Zhao, Zonghan Wu +5
Vision-Language Models (VLMs) frequently suffer from visual perception errors and hallucinations that compromise answer accuracy in complex reasoning tasks. Reinforcement Learning…
LVCG: Learning ECG Representations in the Latent Vectorcardiogram Space
Bosong Huang, Panzhen Zhao, Zengxiang Li +5
Electrocardiography (ECG) is a cornerstone of cardiac assessment, making the learning of informative ECG representations fundamental to tasks ranging from disease diagnosis to clin…
EVLF-FM: Explainable Vision Language Foundation Model for Medicine
Yang Bai, Haoran Cheng, Yang Zhou +40
Despite the promise of foundation models in medical AI, current systems remain limited - they are modality-specific and lack transparent reasoning processes, hindering clinical ado…
Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Yang Zhou, Chrystie Wan Ning Quek, Jun Zhou +22
Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulte…
STMGF: An Effective Spatial-Temporal Multi-Granularity Framework for Traffic Forecasting
Zhengyang Zhao, Haitao Yuan, Nan Jiang +3
Accurate Traffic Prediction is a challenging task in intelligent transportation due to the spatial-temporal aspects of road networks. The traffic of a road network can be affected…