9 papers
ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation
Jiarui Jin, Haoyu Wang, Xingliang Wu +9
Electrocardiography (ECG) serves as an indispensable diagnostic tool in clinical practice, yet existing multimodal large language models (MLLMs) remain unreliable for ECG interpret…
Inflated Excellence or True Performance? Rethinking Medical Diagnostic Benchmarks with Dynamic Evaluation
Xiangxu Zhang, Lei Li, Yanyun Zhou +3
Medical diagnostics is a high-stakes and complex domain that is critical to patient care. However, current evaluations of large language models (LLMs) remain limited in capturing k…
Copy-Paste to Mitigate Large Language Model Hallucinations
Yongchao Long, Xian Wu, Yingying Zhang +3
While Retrieval-Augmented Generation (RAG) enables large language models (LLMs) to generate contextually grounded responses, contextual faithfulness remains challenging as LLMs may…
Beyond Single Models: Mitigating Multimodal Hallucinations via Adaptive Token Ensemble Decoding
Jinlin Li, Yuran Wang, Yifei Yuan +5
Large Vision-Language Models (LVLMs) have recently achieved impressive results in multimodal tasks such as image captioning and visual question answering. However, they remain pron…
From Retrieval to Generation: Unifying External and Parametric Knowledge for Medical Question Answering
Lei Li, Xiao Zhou, Yingying Zhang +1
Medical question answering (QA) requires extensive access to domain-specific knowledge. A promising direction is to enhance large language models (LLMs) with external knowledge ret…
DesignCoder: Hierarchy-Aware and Self-Correcting UI Code Generation with Large Language Models
Yunnong Chen, Shixian Ding, YingYing Zhang +4
Multimodal large language models (MLLMs) have streamlined front-end interface development by automating code generation. However, these models also introduce challenges in ensuring…