Publications

This page shows my publications chronologically. You can also find them on my Google Scholar.

Conference

1. Jingquan Wang, Jun Yin, Xu Han, Yongsheng Mei, Jie Hao, Bin Guo, PB-GRPO: Learning Socially Adaptive LLM Agents from Persona-Driven Simulation with Preference-Batched GRPO, Annual Conference on Language Modeling (COLM) Social Sim workshop, 2026.
2. Yongchang Hao, Jie Hao, Yongsheng Mei, Ze Ye, Junyi Chai, Bin Guo, Benjamin Yao, Chenlei Guo, Lili Mou. VEG: Verbal ε-greedy for Semantic Exploration in Multi-Turn RL Agents, Association for Computational Linguistics (ACL), 2026. [PDF]
3. Egemen Erbayat, Yongsheng Mei, Gina Adam, Suresh Subramaniam, Sean Coffey, Nathaniel D Bastian, Tian Lan, LAMPS: A Learning-based Mobility Planning via Posterior State Inference using Gaussian Cox Process Models, IEEE INFOCOM Workshop on Deep Learning for Wireless Communications, Sensing, and Security (DeepWireless), May 2025. [PDF]
4. Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Carlee Joe-Wong, Gina Adam, Nathaniel D. Bastian, Tian Lan. RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space, Conference on Neural Information Processing Systems (NeurIPS), December 2024. [PDF]
5. Hanhan Zhou, Jingdi Chen, Yongsheng Mei, Gina Adam, Vaneet Aggarwal, Nathaniel D. Bastian, and Tian Lan. Real-time Network Intrusion Detection via Importance Sampled Decision Transformers, Invited Paper, In Proceedings of the 21st IEEE International Conference on Mobile Ad Hoc and Smart Systems (MASS), September 2024. [PDF]
6. Kailash Gogineni, Yongsheng Mei, Karthikeya Gogineni, Peng Wei, Tian Lan, Guru Venkataramani, Characterizing and Optimizing the End-to-End Performance of Multi-Agent Reinforcement Learning Systems, IEEE International Symposium on Workload Characterization (ISWC), August 2024. [PDF]
7. Yongsheng Mei, Mahdi Imani, and Tian Lan, Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data, International Conference on Learning Representations (ICLR), May 2024. [PDF][BibTeX]
8. Yongsheng Mei, Hanhan Zhou, and Tian Lan, Projection-Optimal Monotonic Value Function Factorization in Multi-Agent Reinforcement Learning, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024. [PDF][BibTex]
9. Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina Adam, Nathaniel Bastian, and Tian Lan. Real-time Network Intrusion Detection via Decision Transformers, AAAI workshop on Artificial Intelligence for Cyber Security (AICS), February 2024. [PDF][BibTeX]
10. Yongsheng Mei, Tian Lan, Mahdi Imani, and Suresh Subramaniam, A Bayesian Optimization Framework for Finding Local Optima in Expensive Multi-Modal Functions, European Conference on Artificial Intelligence (ECAI), September 2023. [PDF][BibTeX]
11. Yongsheng Mei, Guru Venkataramani, and Tian Lan, Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor Segmentation, ICML workshop on Machine Learning for Multimodal Healthcare Data (ML4MHD), July 2023. [PDF][BibTeX]
12. Kailash Gogineni, Yongsheng Mei, Peng Wei, Tian Lan, and Guru Venkataramani, AccMER: Accelerating Multi-agent Experience Replay with Cache Locality-aware Prioritization, IEEE International Conference on Application-specific Systems, Architectures, and Processors (ASAP), July 2023. [PDF][BibTeX]
13. Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, and Peng Wei, MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2023. [PDF][BibTeX]
14. Kailash Gogineni, Yongsheng Mei, Guru Venkataramani, and Tian Lan, Verify-Pro: A Framework for Server Authentication Using Communication Protocol Dialects, IEEE Military Communications Conference (MILCOM), September 2022. [PDF][BibTeX]
15. Yongsheng Mei, Kailash Gogineni, Tian Lan, and Guru Venkataramani, MPD: Moving Target Defense through Communication Protocol Dialects, International Conference on Security and Privacy in Communication Networks (SecureComm), September 2021. [PDF][BibTeX]
16. Hongfa Xue, Yongsheng Mei, Kailash Gogineni, Guru Venkataramani, and Tian Lan, Twin-Finder: Integrated Reasoning Engine for Pointer-related Code Clone Detection, International Workshop on Software Clones (IWSC), February 2020. [PDF][BibTeX]

Journal

1. Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal, Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions, Transactions on Machine Learning Research (TMLR), August 2024. [PDF][BibTeX]
2. Yurong Chen, Yongsheng Mei, Tian Lan, and Guru Venkataramani, Exploring Effective Fuzzing Strategies to Analyze Communication Protocols, ACM Digital Threats: Research and Practice (DTRAP), March 2024. [PDF][BibTeX]

Preprint

1. Shu Hong, Yongsheng Mei, Mahdi Imani, Tian Lan, Global Optimization on Graph-Structured Data via Gaussian Processes with Spectral Representations, November 2025. [PDF]
2. Yongsheng Mei, Liangqi Yuan, Dong-Jun Han, Kevin S Chan, Christopher Brinton, and Tian Lan. Continual Federated Learning with Conditional Diffusion Models as Replay, May 2024. [PDF]