Siliang Zeng

According to our database, Siliang Zeng authored at least 23 papers between 2006 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Aligning Frozen LLMs by Reinforcement Learning: An Iterative Reweight-then-Optimize Approach.

Xinnan Zhang, Chenliang Li, Siliang Zeng, Jiaxiang Li, Zhongruo Wang, Kaixiang Lin, Songtao Lu, Alfredo García, Mingyi Hong

CoRR, June, 2025

Reinforcing Multi-Turn Reasoning in LLM Agents via Turn-Level Credit Assignment.

Siliang Zeng, Quan Wei, William Brown, Oana Frunza, Yuriy Nevmyvaka, Mingyi Hong

CoRR, May, 2025

From Demonstrations to Rewards: Alignment Without Explicit Human Preferences.

Siliang Zeng, Yao Liu, Huzefa Rangwala, George Karypis, Mingyi Hong, Rasool Fakoor

CoRR, March, 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

Trans. Mach. Learn. Res., 2025

Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees.

Siliang Zeng, Mingyi Hong, Alfredo García

Oper. Res., 2025

Joint Reward and Policy Learning with Demonstrations and Human Feedback Improves Alignment.

Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo García, Mingyi Hong

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality.

Ruijia Zhang, Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Joint Demonstration and Preference Learning Improves Policy Alignment with Human Feedback.

Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo García, Mingyi Hong

CoRR, 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 García, Mingyi Hong

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Understanding Expertise through Demonstrations: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning.

Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong

CoRR, 2023

When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning.

Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProfLLM: A framework for adapting offline large language models to few-shot expert knowledge.

Hao Wang, Siliang Zeng, Zhenwei Xue, Xinglin Zhu, Fei Wu, Ning Wang

Proceedings of the 4th International Conference on Artificial Intelligence and Computer Engineering, 2023

A Bayesian Approach to Robust Inverse Reinforcement Learning.

Ran Wei, Siliang Zeng, Chenliang Li, Alfredo García, Anthony D. McDonald, Mingyi Hong

Proceedings of the Conference on Robot Learning, 2023

2022

On the Divergence of Decentralized Nonconvex Optimization.

Mingyi Hong, Siliang Zeng, Junyu Zhang, Haoran Sun

SIAM J. Optim., December, 2022

Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees.

Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization.

Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees.

Siliang Zeng, Tianyi Chen, Alfredo García, Mingyi Hong

Proceedings of the Learning for Dynamics and Control Conference, 2022

2021

A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization.

Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

On the Divergence of Decentralized Non-Convex Optimization.

Mingyi Hong, Siliang Zeng, Junyu Zhang, Haoran Sun

CoRR, 2020

Multi-Agent Reinforcement Learning for Adaptive Routing: A Hybrid Method using Eligibility Traces.

Siliang Zeng, Xingfei Xu, Yi Chen

Proceedings of the 16th IEEE International Conference on Control & Automation, 2020

Network-Level System Performance Prediction Using Deep Neural Networks with Cross-Layer Information.

Qi Cao, Siliang Zeng, Man-On Pun, Yi Chen

Proceedings of the 2020 IEEE International Conference on Communications, 2020

2006

A new In-network data aggregation technology of wireless sensor networks.

Jianbo Xu, Siliang Zeng, Fengjiao Qu

Proceedings of the 2006 International Conference on Semantics, 2006