1. 自然科学基金面上项目《谱极值图论的若干经典问题和新问题》，50万，2022.01-2025.12. 【参与】

2.  自然科学基金面上项目《高维数据统计推断中协方差矩阵估计的优化模型与算法研究

》，52万，2020.01-2023.12. 【参与】

3. 自然科学基金面上项目《非干预式感知的学业求助资源推荐研究》，50万，2019.01-2023.12. 【参与】

4. 联合基金项目《政府治理大数据共享与融合技术研究》，581万，2019.01-2023.12. 【参与】

 5.  青年科学基金项目《大规模结构矩阵的预处理方法与理论及其在压缩感知中的应用》，23万，2019.01-2021.12. 【参与】

6. 校企合作《自然语言处理技术在融资融券业务中的应用》，24万，2021.08-2022.06. 【主要完成人】

会议论文：

1. Kangyang Luo, Yuzhuo Bai, Shuzheng Si, Cheng Gao, Zhitong Wang, Yingli Shen, Wenhao Li, Zhu Liu, Yufeng Han, Jiayi Wu, Cunliang Kong, Maosong Sun. ImCoref-CeS: An Improved Lightweight Pipeline for Coreference Resolution with LLM-based Checker-Splitter Refinement[C]. The 64rd Annual Meeting of the Association for Computational Linguistics (ACL), 2026.【CCF-A, Oral】

2.  Kangyang Luo, Shuzheng Si, Yuzhuo Bai, Cheng Gao, Zhitong Wang, Cheng Huang, Yingli Shen, Yufeng Han, Wenhao Li, Cunliang Kong, Maosong Sun. MEIC-DT: Memory-Efficient Incremental Clustering for Long-Text Coreference Resolution with Dual-Threshold Constraints[C]. Findings of the 64rd Annual Meeting of the Association for Computational Linguistics (ACL), 2026.【CCF-A】

3.   Kangyang Luo, Yuzhuo Bai, Cheng Gao, Shuzheng Si, Yingli Shen, Zhu Liu, Zhitong Wang, Cunliang Kong, Wenhao Li, Yufei Huang, Ye Tian, Xuantang Xiong, Lei Han, Maosong Sun. GLTW: Joint Improved Graph Transformer and LLM via Three-Word Language for Knowledge Graph Completion[C]. Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.【CCF-A】

 4.   Kangyang Luo, Zichen Ding, Zhenmin Weng, Lingfeng Qiao, Meng Zhao, Xiang Li, di yin, Jinlong Shu. Let's Be Self-generated via Step by Step: A Curriculum Learning Approach to Automated Reasoning with Large Language Models[C]. Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.【CCF-A】

 5.   Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao. Data-Free Robustness Distillation for Heterogeneous Federated Learning [C]. Advances in Neural Information Processing Systems (NeurIPS), 2023. 【CCF-A】

 6.   Kangyang Luo, Xiang Li, Yunshi Lan, and Ming Gao. GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting [C]. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. 【CCF-A, Highlight论文, 前2.5%】

7.  Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao. DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning [C]. IEEE International Conference on Data Mining (ICDM), 2024. 【CCF-B】

8.  Kangyang Luo, Kunkun Zhang, Shengbo Zhang, et al. Decentralized Local Updates with Dual-Slow Estimation and Momentum-based Variance-Reduction for Non-Convex Optimization [C]. European Conference on Artificial Intelligence (ECAI), 2023.  【CCF-B】

9.  Yuzhuo Bai, Shuzheng Si, Kangyang Luo, Qingyi Wang, Wenhao Li, Gang Chen, Fanchao Qi, Maosong Sun. InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs on Grounding Documents[C]. Conference on Empirical Methods in Natural Language Processing: EMNLP, 2026. 【CCF-B】

10.  Jiayi Wu, Ruobing Xie, Zeqian Huang, Lei Jiang, Can Xu, Kangyang Luo, Bochen Lin, Ming Gao, Xiang Li. Negative Advantages Is a Double-Edged Sword: Calibrating advantages in GRPO for Search Agents[C]. Findings of Conference on Empirical Methods in Natural Language Processing: EMNLP, 2026. 【CCF-B】

11.  Shuzheng Si, Haozhe Zhao, Kangyang Luo, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun. A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks [C]. The 64rd Annual Meeting of the Association for Computational Linguistics (ACL), 2026.【CCF-A, Oral】

12.  Shuzheng Si, Qingyi Wang, Haozhe Zhao, Yuzhuo Bai, Guanqiao Chen, Kangyang Luo, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun. FaithLens: Detecting and Explaining Faithfulness Hallucination[C]. Findings of the 64rd Annual Meeting of the Association for Computational Linguistics (ACL), 2026.【CCF-A】

 13. Shuzheng Si, Haozhe Zhao, Cheng Gao, Yuzhuo Bai, Zhitong Wang, Bofei Gao, Kangyang Luo, Wenhao Li, Yufei Huang, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun. Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning [C]. The 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026.【CCF-A, Oral】

14. Yingli Shen, Wen Lai, Shuo Wang, Xueren Zhang, Kangyang Luo, Alexander Fraser, Maosong Sun. DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly Detection [C]. Advances in Neural Information Processing Systems (NeurIPS), 2025. 【CCF-A】

 15. Shuzheng Si, Haozhe Zhao, Gang Chen, Yunshui Li, Kangyang Luo, Chuancheng Lv, Kaikai An, Fanchao Qi, Baobao Chang, Maosong Sun. GATEAU: Selecting Influential Sample for Long Context Alignment[C]. Conference on Empirical Methods in Natural Language Processing: EMNLP, 2025.【CCF-B, SAC Highlights Award, 前0.5%】

 16. Yingli Shen, Wen Lai, Shuo Wang, Kangyang Luo, Alexander Fraser, Maosong Sun. From Unaligned to Aligned: Scaling Multilingual LLMs with Multi-Way Parallel Corpora [C]. Conference on Empirical Methods in Natural Language Processing: EMNLP, 2025.【CCF-B】

17.  Shuzheng Si, Haozhe Zhao, Gang Chen, Cheng Gao, Yuzhuo Bai, Zhitong Wang, Kaikai An, Kangyang Luo, Chen Qian, Fanchao Qi, Baobao Chang, Maosong Sun. Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering[C]. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.【CCF-A】

18.  Zhitong Wang, Cheng Gao, Yufei Huang, Shuzheng Si, Kangyang Luo, Yuzhuo Bai, Wenhao Li, Tangjian Duan, Chuancheng Lv, Guoshan Lu, Gang Chen, Fanchao Qi, Chaojun Xiao, Maosong Sun. Document Segmentation Matters for Retrieval-Augmented Generation[C]. Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.【CCF-A】

19. Jianxiang Yu, Zichen Ding, Jiaqi Tan, Kangyang Luo, Zhenmin Weng, Chenghua Gong, Long Zeng, RenJing Cui, Chengcheng Han, Qiushi Sun, Zhiyong Wu, Yunshi Lan, Xiang Li. Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis [C]. Findings of Conference on Empirical Methods in Natural Language Processing: EMNLP, 2024, 10164-10184.【CCF-B】

20. Keren Tan, Kangyang Luo, Yunshi Lan, Zheng Yuan and Jinlong Shu. An LLM-Enhanced Adversarial Editing System for Lexical Simplification [C]. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024, 1136-1146. 【CCF-B】

21. Cheng Gao, Cheng Huang, Kangyang Luo, Yuzhuo Bai, Shuzheng Si,  Zhitong Wang, Yingli Shen, Wenhao Li, Zhu Liu, Yufeng Han, Jiayi Wu, Cunliang Kong, Maosong Sun. KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning[C]. Conference On Language Modeling (COLM), 2026. 

期刊论文：

1. Wenhui Liu, Kangyang Luo, Zhijian Wu, Shanfeng Hao, Dingjiang Huang. Mitigating OOD Overoptimism via In-Sample Value Function in Offline Reinforcement Learning[J]. Neural Networks, 2026: 108763. 【SCI-Q1,中科院1区, CCF-B】    

2. Renrong Shao, Wei Zhang, Kangyang Luo, Qin Li, Jun Wang. AudoFormer: An Efficient Transformer with Consistent Auxiliary Domain for Source-free Domain Adaptation[J]. IEEE Transactions on Image Processing, 2025. 【SCI-Q1,中科院1区, CCF-A】    

3. Zhangshuang Sun, Xuerui Gao, Kangyang Luo, Yanqin Bai, Jiyuan Tao, Guoqiang Wang. Enhancing High-Dimensional Dynamic Conditional Angular Correlation Model Based on GARCH Family Models: Comparative Performance Analysis for Portfolio Optimization[J]. Finance Research Letters, 2025, 75: 106808.【SCI-Q1,中科院2区】    

4. Xiaojin Xie, Kangyang Luo, Guoqiang Wang. A New L₁ Multi-Kernel Learning Support Vector Regression Ensemble Algorithm With AdaBoost [J], IEEE Access, 2022, 10: 20375-20384.【SCI-Q2, 中科院4区】    

5. Xiaojin Xie, Kangyang Luo, Zhixiang Yin, Guoqiang Wang. Nonlinear combinational dynamic transmission rate model and its application in global covid-19 epidemic prediction and analysis [J], Mathematics, 2021, 9(18): 2307. 【SCI-Q1, 中科院4区】    

6. Kangyang Luo, Guoqiang Wang, Qian Li, and J.Y. Tao. An Improved SVM-RFE based on F-statistic and mPDC for Gene Selection in Cancer Classification[J]. IEEE Access, 2019, 7(1): 147617-147628. 【SCI-Q2, 中科院3区】    

7. 张田华, 罗康洋. 基于集成学习的上市公司高送转预测实证研究[J], 计算机工程与应用, 2022, 58 (10): 255-262. 【CCF-B, 北大核心, CSCD扩展版】    

8. 谢晓金，罗康洋，张怡，金建炳，林海翔，殷志祥，王国强. 非线性组合动态传播率模型与我国 COVID-19 疫情分析和预测[J], 运筹学学报, 2021, 25(1):17-30.【北大核心，CSCD】    

9. 罗康洋, 王国强. 基于改进的MRMR算法和代价敏感分类的财务预警研究[J], 统计与信息论坛, 2020, 25(3): 77-85. 【北大核心，CSSCI】    

10. 罗康洋, 王国强. L-SMOTE与SVM结合的不平衡数据集分类研究[J], 计算机工程与应用, 2019, 55(17): 55-62. 【CCF-B, 北大核心, CSCD扩展版】