1 citations · 1 across the 8 of their papers we have counts for
12 papers
ECG-RSI: Recursive Self-Improvement through Targeted Electrocardiogram Waveform Evolution
Xiaoliang Wang, Zhuo Chen, Chuanyang Zheng +9
Electrocardiogram (ECG) models need supervision that targets evolving weaknesses and remains faithful to waveform evidence. We introduce ECG-RSI, a recursive self-improvement frame…
MedEvo: Medical Reasoning Evolution through Knowledge Navigation
Xiaoliang Wang, Zhuo Chen, Chuanyang Zheng +11
Medical multimodal reasoning models are typically trained on teacher-generated rationales, discarding the valid reasoning in students' own failed trajectories, while general-domain…
ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering
Taojie Zhu, Yuan Xia, Tao Sun +8
Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many open-ended medical question…
ClinAlign: Scaling Healthcare Alignment from Clinician Preference
Shiwei Lyu, Xidong Wang, Lei Liu +6
Although large language models (LLMs) demonstrate expert-level medical knowledge, aligning their open-ended outputs with fine-grained clinician preferences remains challenging. Exi…
PulseMind: A Multi-Modal Medical Model for Real-World Clinical Diagnosis
Jiao Xu, Junwei Liu, Jiangwei Lao +9
Recent advances in medical multi-modal models focus on specialized image analysis like dermatology, pathology, or radiology. However, they do not fully capture the complexity of re…
MLB: A Scenario-Driven Benchmark for Evaluating Large Language Models in Clinical Applications
Qing He, Dongsheng Bi, Jianrong Lu +20
The proliferation of Large Language Models (LLMs) presents transformative potential for healthcare, yet practical deployment is hindered by the absence of frameworks that assess re…
EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis
Yusheng Liao, Chaoyi Wu, Junwei Liu +12
Electronic Health Records (EHRs) contain rich yet complex information, and their automated analysis is critical for clinical decision-making. Despite recent advances of large langu…
Evolving Interactive Diagnostic Agents in a Virtual Clinical Environment
Pengcheng Qiu, Chaoyi Wu, Junwei Liu +11
We present a framework for training large language models (LLMs) as diagnostic agents with reinforcement learning, enabling them to manage multi-turn interactive diagnostic process…
LLM Encoder vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA
Houji Jin, Negin Ashrafi, Armin Abdollahi +5
The rapid growth of large language models (LLMs) has heightened the demand for accurate detection of AI-generated text, particularly in languages like Chinese, where subtle linguis…
KG2QA: Knowledge Graph-enhanced Retrieval-augmented Generation for Communication Standards Question Answering
Zhongze Luo, Weixuan Wan, Tianya Zhang +2
The rapid evolution of communication technologies has led to an explosion of standards, rendering traditional expert-dependent consultation methods inefficient and slow. To address…
An LLM-Driven Multi-Agent Debate System for Mendelian Diseases
Xinyang Zhou, Yongyong Ren, Qianqian Zhao +15
Accurate diagnosis of Mendelian diseases is crucial for precision therapy and assistance in preimplantation genetic diagnosis. However, existing methods often fall short of clinica…
Segmented Harmonic Loss: Handling Class-Imbalanced Multi-Label Clinical Data for Medical Coding with Large Language Models
Surjya Ray, Pratik Mehta, Hongen Zhang +5
The precipitous rise and adoption of Large Language Models (LLMs) have shattered expectations with the fastest adoption rate of any consumer-facing technology in history. Healthcar…