Zeng, Siliang

17 publications

TMLR 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

ICLRW 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

ICLR 2025 Joint Reward and Policy Learning with Demonstrations and Human Feedback Improves Alignment Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo Garcia, Mingyi Hong

ICLRW 2025 Reinforcement Learning in Inference Time: A Perspective from Successive Policy Iterations Xinnan Zhang, Chenliang Li, Siliang Zeng, Jiaxiang Li, Zhongruo Wang, Songtao Lu, Alfredo Garcia, Mingyi Hong

AISTATS 2025 Understanding Inverse Reinforcement Learning Under Overparameterization: Non-Asymptotic Analysis and Global Optimality Ruijia Zhang, Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPS 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo Garcia, Mingyi Hong

ICMLW 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment Jiaxiang Li, Siliang Zeng, Hoi To Wai, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPSW 2024 LLM Alignment Through Successive Policy Re-Weighting (SPR) Xinnan Zhang, Siliang Zeng, Jiaxiang Li, Kaixiang Lin, Mingyi Hong

NeurIPSW 2024 Learning Reward and Policy Jointly from Demonstration and Preference Improves Alignment Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo Garcia, Mingyi Hong

CoRL 2023 A Bayesian Approach to Robust Inverse Reinforcement Learning Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony D McDonald, Mingyi Hong

ICMLW 2023 Robust Inverse Reinforcement Learning Through Bayesian Theory of Mind Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony McDonald, Mingyi Hong

NeurIPS 2023 When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPS 2022 A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong

L4DC 2022 Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees Siliang Zeng, Tianyi Chen, Alfredo Garcia, Mingyi Hong

NeurIPS 2022 Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

ICMLW 2022 Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong

NeurIPS 2021 A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang