| Towards unifying behavioral and response diversity for open-ended learning in zero-sum games X Liu, H Jia, Y Wen, Y Hu, Y Chen, C Fan, Z Hu, Y Yang Advances in Neural Information Processing Systems 34, 941-952, 2021 | 71* | 2021 |
| Do LLM Agents Have Regret? A Case Study in Online Learning and Games C Park*, X Liu*, A Ozdaglar, K Zhang The Thirteenth International Conference on Learning Representations, 2025 | 16 | 2025 |
| Is poisoning a real threat to LLM alignment? Maybe more so than you think P Pathmanathan, S Chakraborty, X Liu, Y Liang, F Huang Proceedings of the AAAI Conference on Artificial Intelligence, 2025 | 8 | 2025 |
| Partially observable multi-agent RL with (quasi-) efficiency: the blessing of information sharing X Liu, K Zhang International Conference on Machine Learning, 22370-22419, 2023 | 8 | 2023 |
| Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL X Liu, S Chakraborty, Y Sun, F Huang The Twelfth International Conference on Learning Representations, 2023 | 6* | 2023 |
| Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies X Liu, C Deng, Y Sun, Y Liang, F Huang The Twelfth International Conference on Learning Representations, 2023 | 6 | 2023 |
| Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations Y Liang, Y Sun, R Zheng, X Liu, T Sandholm, F Huang, S McAleer The Twelfth International Conference on Learning Representations, 2023 | 5 | 2023 |
| Provable Partially Observable Reinforcement Learning with Privileged Information Y Cai*, X Liu*, A Oikonomou*, K Zhang* The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 2 | 2024 |
