Runlong Zhou

According to our database, Runlong Zhou authored at least 15 papers between 2021 and 2025.

Collaborative distances:

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

2025

Sharp Gap-Dependent Variance-Aware Regret Bounds for Tabular MDPs.

Shulun Chen, Runlong Zhou, Zihan Zhang, Maryam Fazel, Simon S. Du

CoRR, June, 2025

Understanding the Performance Gap in Preference Learning: A Dichotomy of RLHF and DPO.

Ruizhe Shi, Minhak Song, Runlong Zhou, Zihan Zhang, Maryam Fazel, Simon S. Du

CoRR, May, 2025

CASCADE Your Datasets for Cross-Mode Knowledge Retrieval of Language Models.

Runlong Zhou, Yi Zhang

CoRR, April, 2025

Extragradient Preference Optimization (EGPO): Beyond Last-Iterate Convergence for Nash Learning from Human Feedback.

Runlong Zhou, Maryam Fazel, Simon S. Du

CoRR, March, 2025

The Crucial Role of Samplers in Online Direct Preference Optimization.

Ruizhe Shi, Runlong Zhou, Simon Shaolei Du

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Transformers are Efficient Compilers, Provably.

Xiyu Zhai, Runlong Zhou, Liao Zhang, Simon Shaolei Du

CoRR, 2024

Multi-Agent Reinforcement Learning from Human Feedback: Data Coverage and Algorithmic Techniques.

Natalia Zhang, Xinqi Wang, Qiwen Cui, Runlong Zhou, Sham M. Kakade, Simon S. Du

CoRR, 2024

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning.

Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Reflect-RL: Two-Player Online RL Fine-Tuning for LMs.

Runlong Zhou, Simon S. Du, Beibin Li

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization.

Runlong Zhou, Zelin He, Yuandong Tian, Yi Wu, Simon Shaolei Du

Trans. Mach. Learn. Res., 2023

Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments.

Runlong Zhou, Zihan Zhang, Simon Shaolei Du

Proceedings of the International Conference on Machine Learning, 2023

Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes.

Runlong Zhou, Ruosong Wang, Simon Shaolei Du

Proceedings of the International Conference on Machine Learning, 2023

2022

Horizon-Free Reinforcement Learning for Latent Markov Decision Processes.

Runlong Zhou, Ruosong Wang, Simon S. Du

CoRR, 2022

Understanding Curriculum Learning in Policy Optimization for Solving Combinatorial Optimization Problems.

Runlong Zhou, Yuandong Tian, Yi Wu, Simon S. Du

CoRR, 2022

2021

Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret.

Jean Tarbouriech, Runlong Zhou, Simon S. Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric

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