Hongxin Ding

According to our database, Hongxin Ding authored at least 13 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Toward Better EHR Reasoning in LLMs: Reinforcement Learning with Expert Attention Guidance.

Yue Fang, Yuxin Guo, Jiaran Gao, Hongxin Ding, Xinke Jiang, Weibin Liao, Yongxin Xu, Yinghao Zhu, Zhibang Yang, Liantao Ma, Junfeng Zhao, Yasha Wang

CoRR, August, 2025

ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs.

Hongxin Ding, Baixiang Huang, Yue Fang, Weibin Liao, Xinke Jiang, Zheng Li, Junfeng Zhao, Yasha Wang

CoRR, August, 2025

Fed-GAN: Federated Generative Adversarial Network With Privacy-Preserving for Cross-Device Scenarios.

Song Han, Hongxin Ding, Shuai Zhao, Siqi Ren, Shengke Zeng, Mengqi Xue, Ruili Wang

IEEE Trans. Dependable Secur. Comput., 2025

HyKGE: A Hypothesis Knowledge Graph Enhanced RAG Framework for Accurate and Reliable Medical LLMs Responses.

Xinke Jiang, Ruizhe Zhang, Yongxin Xu, Rihong Qiu, Yue Fang, Zhiyuan Wang, Jinyi Tang, Hongxin Ding, Xu Chu, Junfeng Zhao, Yasha Wang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

DearLLM: Enhancing Personalized Healthcare via Large Language Models-Deduced Feature Correlations.

Yongxin Xu, Xinke Jiang, Xu Chu, Rihong Qiu, Yujie Feng, Hongxin Ding, Junfeng Zhao, Yasha Wang, Bing Xie

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Practical and Robust Federated Learning With Highly Scalable Regression Training.

Song Han, Hongxin Ding, Shuai Zhao, Siqi Ren, Zhibo Wang, Jianhong Lin, Shuhao Zhou

IEEE Trans. Neural Networks Learn. Syst., October, 2024

3DS: Decomposed Difficulty Data Selection's Case Study on LLM Medical Domain Adaptation.

Hongxin Ding, Yue Fang, Runchuan Zhu, Xinke Jiang, Jinyang Zhang, Yongxin Xu, Xu Chu, Junfeng Zhao, Yasha Wang

CoRR, 2024

ProtoMix: Augmenting Health Status Representation Learning via Prototype-based Mixup.

Yongxin Xu, Xinke Jiang, Xu Chu, Yuzhen Xiao, Chaohe Zhang, Hongxin Ding, Junfeng Zhao, Yasha Wang, Bing Xie

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023

Think and Retrieval: A Hypothesis Knowledge Graph Enhanced Medical Large Language Models.

Xinke Jiang, Ruizhe Zhang, Yongxin Xu, Rihong Qiu, Yue Fang, Zhiyuan Wang, Jinyi Tang, Hongxin Ding, Xu Chu, Junfeng Zhao, Yasha Wang

CoRR, 2023

A ModelOps-based Framework for Intelligent Medical Knowledge Extraction.

Hongxin Ding, Peinie Zou, Zhiyuan Wang, Junfeng Zhao, Yasha Wang, Qiang Zhou

CoRR, 2023

SeqCare: Sequential Training with External Medical Knowledge Graph for Diagnosis Prediction in Healthcare Data.

Yongxin Xu, Xu Chu, Kai Yang, Zhiyuan Wang, Peinie Zou, Hongxin Ding, Junfeng Zhao, Yasha Wang, Bing Xie

Proceedings of the ACM Web Conference 2023, 2023

VecoCare: Visit Sequences-Clinical Notes Joint Learning for Diagnosis Prediction in Healthcare Data.

Yongxin Xu, Kai Yang, Chaohe Zhang, Peinie Zou, Zhiyuan Wang, Hongxin Ding, Junfeng Zhao, Yasha Wang, Bing Xie

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

KerPrint: Local-Global Knowledge Graph Enhanced Diagnosis Prediction for Retrospective and Prospective Interpretations.

Kai Yang, Yongxin Xu, Peinie Zou, Hongxin Ding, Junfeng Zhao, Yasha Wang, Bing Xie

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023