Xinke Jiang

According to our database, Xinke Jiang authored at least 27 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• 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

STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution Generalization.

Haoyu Zhang, Wentao Zhang, Hao Miao, Xinke Jiang, Yuchen Fang, Yifan Zhang

CoRR, May, 2025

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation.

Runchuan Zhu, Xinke Jiang, Jiang Wu, Zhipeng Ma, Jiahe Song, Fengshuo Bai, Dahua Lin, Lijun Wu, Conghui He

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective.

Yuchen Fang, Yuxuan Liang, Bo Hui, Zezhi Shao, Liwei Deng, Xu Liu, Xinke Jiang, Kai Zheng

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning.

Yongxin Xu, Ruizhe Zhang, Xinke Jiang, Yujie Feng, Yuzhen Xiao, Xinyu Ma, Runchuan Zhu, Xu Chu, Junfeng Zhao, Yasha Wang

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

TC-RAG: Turing-Complete RAG's Case study on Medical LLM Systems.

Xinke Jiang, Yue Fang, Rihong Qiu, Haoyu Zhang, Yongxin Xu, Hao Chen, Wentao Zhang, Ruizhe Zhang, Yuchen Fang, Xinyu Ma, Xu Chu, Junfeng Zhao, Yasha Wang

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

Time Series Supplier Allocation via Deep Black-Litterman Model.

Xinke Jiang, Wentao Zhang, Yuchen Fang, Xiaowei Gao, Hao Chen, Haoyu Zhang, Dingyi Zhuang, Jiayuan Luo

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

KnowPO: Knowledge-Aware Preference Optimization for Controllable Knowledge Selection in Retrieval-Augmented Language Models.

Ruizhe Zhang, Yongxin Xu, Yuzhen Xiao, Runchuan Zhu, Xinke Jiang, Xu Chu, Junfeng Zhao, Yasha Wang

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

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

TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems.

Xinke Jiang, Yue Fang, Rihong Qiu, Haoyu Zhang, Yongxin Xu, Hao Chen, Wentao Zhang, Ruizhe Zhang, Yuchen Fang, Xu Chu, Junfeng Zhao, Yasha Wang

CoRR, 2024

CaT-GNN: Enhancing Credit Card Fraud Detection via Causal Temporal Graph Neural Networks.

Yifan Duan, Guibin Zhang, Shilong Wang, Xiaojiang Peng, Ziqi Wang, Junyuan Mao, Hao Wu, Xinke Jiang, Kun Wang

CoRR, 2024

Kuaiji: the First Chinese Accounting Large Language Model.

Jiayuan Luo, Songhua Yang, Xiaoling Qiu, Panyu Chen, Yufei Nai, Wenxuan Zeng, Wentao Zhang, Xinke Jiang

CoRR, 2024

Timeseries Suppliers Allocation Risk Optimization via Deep Black Litterman Model.

Jiayuan Luo, Wentao Zhang, Yuchen Fang, Xiaowei Gao, Dingyi Zhuang, Hao Chen, Xinke Jiang

CoRR, 2024

Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation.

Ruizhe Zhang, Xinke Jiang, Yuchen Fang, Jiayuan Luo, Yongxin Xu, Yichen Zhu, Xu Chu, Junfeng Zhao, Yasha Wang

CoRR, 2024

Incomplete Graph Learning via Attribute-Structure Decoupled Variational Auto-Encoder.

Xinke Jiang, Zidi Qin, Jiarong Xu, Xiang Ao

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

RAGraph: A General Retrieval-Augmented Graph Learning Framework.

Xinke Jiang, Rihong Qiu, Yongxin Xu, Wentao Zhang, Yichen Zhu, Ruizhe Zhang, Yuchen Fang, Chu Xu, Junfeng Zhao, Yasha Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 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

FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis.

Songhua Yang, Xinke Jiang, Hanjie Zhao, Wenxuan Zeng, Hongde Liu, Yuxiang Jia

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 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

Spatiotemporal Graph Neural Networks with Uncertainty Quantification for Traffic Incident Risk Prediction.

Xiaowei Gao, Xinke Jiang, Dingyi Zhuang, Huanfa Chen, Shenhao Wang, James Haworth

CoRR, 2023

Uncertainty Quantification in the Road-level Traffic Risk Prediction by Spatial-Temporal Zero-Inflated Negative Binomial Graph Neural Network(STZINB-GNN).

Xiaowei Gao, James Haworth, Dingyi Zhuang, Huanfa Chen, Xinke Jiang

CoRR, 2023

Uncertainty Quantification in the Road-Level Traffic Risk Prediction by Spatial-Temporal Zero-Inflated Negative Binomial Graph Neural Network(STZINB-GNN) (Short Paper).

Xiaowei Gao, James Haworth, Dingyi Zhuang, Huanfa Chen, Xinke Jiang

Proceedings of the 12th International Conference on Geographic Information Science, 2023

Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction.

Xinke Jiang, Dingyi Zhuang, Xianghui Zhang, Hao Chen, Jiayuan Luo, Xiaowei Gao

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning.

Rongfan Li, Ting Zhong, Xinke Jiang, Goce Trajcevski, Jin Wu, Fan Zhou

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022