| 2025 | EMNLP | Faster In-Context Learning for LLMs via N-Gram Trie Speculative Decoding. | Jinglin Chen, Qiwei Li, Zuchao Li, Baoyuan Qi, Guoming Liu, Haojun Ai, Hai Zhao, Ping Wang |
| 2023 | CISS | Extended Abstract: Learning in Low-rank MDPs with Density Features. | Audrey Huang, Jinglin Chen, Nan Jiang |
| 2023 | ICML | Reinforcement Learning in Low-rank MDPs with Density Features. | Audrey Huang, Jinglin Chen, Nan Jiang |
| 2022 | ICLR | Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. | Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu |
| 2022 | UAI | Offline reinforcement learning under value and density-ratio realizability: The power of gaps. | Jinglin Chen, Nan Jiang |
| 2021 | AAAI | Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration. | Priyank Agrawal, Jinglin Chen, Nan Jiang |
| 2019 | ICLR | Accelerating Nonconvex Learning via Replica Exchange Langevin diffusion. | Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang |
| 2019 | ICML | Information-Theoretic Considerations in Batch Reinforcement Learning. | Jinglin Chen, Nan Jiang |
| 2018 | IJCAI | Efficient Localized Inference for Large Graphical Models. | Jinglin Chen, Jian Peng, Qiang Liu |