10 papers
Escaping the BLEU Trap: A Signal-Grounded Framework with Decoupled Semantic Guidance for EEG-to-Text Decoding
Yuchen Wang, Haonan Wang, Yu Guo +2
Decoding natural language from non-invasive EEG signals is a promising yet challenging task. However, current state-of-the-art models remain constrained by three fundamental issues…
Divide-then-Diagnose: Weaving Clinician-Inspired Contexts for Ultra-Long Capsule Endoscopy Videos
Bowen Liu, Li Yang, Shanshan Song +6
Capsule endoscopy (CE) enables non-invasive gastrointestinal screening, but current CE research remains largely limited to frame-level classification and detection, leaving video-l…
Adapting 2D Multi-Modal Large Language Model for 3D CT Image Analysis
Yang Yu, Dunyuan Xu, Yaoqian Li +3
3D medical image analysis is of great importance in disease diagnosis and treatment. Recently, multimodal large language models (MLLMs) have exhibited robust perceptual capacity, s…
RadHiera: Semantic Hierarchical Reinforcement Learning for Medical Report Generation
Bodong Du, Honglong Yang, Xiaomeng Li
Vision-language models have shown promising results in radiology report generation. However, most existing methods generate reports as flat text and do not explicitly model the sem…
Which Tool Response Should I Trust? Tool-Expertise-Aware Chest X-ray Agent with Multimodal Agentic Learning
Zheang Huai, Honglong Yang, Xiaomeng Li
AI agents with tool-use capabilities show promise for integrating the domain expertise of various tools. In the medical field, however, tools are usually AI models that are inheren…
OFL-SAM2: Prompt SAM2 with Online Few-shot Learner for Efficient Medical Image Segmentation
Meng Lan, Lefei Zhang, Xiaomeng Li
The Segment Anything Model 2 (SAM2) has demonstrated remarkable promptable visual segmentation capabilities in video data, showing potential for extension to medical image segmenta…