Publications · Miao Lu

INFUSER: Influence-Guided Self-Evolution Improves Reasoning

Siyu Chen, Miao Lu, Beining Wu, Heejune Sheen, Fengzhuo Zhang, Shuangning Li, Zhiyuan Li, Jose Blanchet, Tianhao Wang, Zhuoran Yang

arXiv preprint, Jun 2026

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A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training

Junze Ye*, Jiayi Cheng*, Miao Lu*, Michal Mankowski, Jose Blanchet, Mohsen Bayati

ICML Workshop on RL from World Feedback (RLxF) 2026

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Towards Understanding Momentum Acceleration in River-Valley Loss Landscape

Miao Lu, Zeyu Bian, Kaiyue Wen, Beining Wu, Siyu Chen, Tianhao Wang, Zhiyuan Li

ICML Workshop on High-dimensional Learning Dynamics (HiLD) 2026 Spotlight

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Scaling Long-Horizon LLM Agent via Context Folding

Weiwei Sun, Miao Lu, Zhan Ling, Kang Liu, Xuesong Yao, Yiming Yang, Jiecao Chen

International Conference on Machine Learning (ICML) 2026

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Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression

Xingwu Chen, Miao Lu, Beining Wu, Difan Zou

NeurIPS Workshop on Foundations of Reasoning in Language Models (FoRLM) 2025

International Conference on Machine Learning (ICML) 2026

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Robust Assortment Optimization from Observational Data

Miao Lu, Yuxuan Han, Han Zhong, Zhengyuan Zhou, Jose Blanchet

arXiv preprint, Feb 2026

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Beyond the Context Window: Scaling Agentic RL via End-to-end Optimized Context Compression

Miao Lu, Weiwei Sun, Weihua Du, Zhan Ling, Xuesong Yao, Kang Liu, Jiecao Chen

Association for Computational Linguistics (ACL) 2026

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Learning an Optimal Assortment Policy under Observational Data

Yuxuan Han, Han Zhong, Miao Lu, Jose Blanchet, Zhengyuan Zhou

Under review in Management Science (MS)

arXiv preprint, Feb 2025

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Can Neural Networks Achieve Optimal Computational-Statistical Tradeoff? An Analysis on Single-Index Model

Siyu Chen*, Beining Wu*, Miao Lu, Zhuoran Yang, Tianhao Wang

NeurIPS Workshop on Mathematics of Modern ML (M3L) 2024 Oral

International Conference on Learning Representations (ICLR) 2025 Oral

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Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer

Zhihan Liu*, Miao Lu*, Shenao Zhang, Boyi Liu, Hongyi Guo, Yingxiang Yang, Jose Blanchet, Zhaoran Wang

ICML Workshop on Aligning RL Experimentalists and Theorists (ARLET) 2024

Neural Information Processing Systems (NeurIPS) 2024

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Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm

Miao Lu*, Han Zhong*, Tong Zhang, Jose Blanchet

ICML Workshop on Aligning RL Experimentalists and Theorists (ARLET) 2024

Neural Information Processing Systems (NeurIPS) 2024

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Benign Oscillation of Stochastic Gradient Descent with Large Learning Rates

Miao Lu*, Beining Wu*, Xiaodong Yang, Difan Zou

NeurIPS Workshop on Mathematics of Modern ML (M3L) 2023

International Conference on Learning Representations (ICLR) 2024

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Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration

Zhihan Liu*, Miao Lu*, Wei Xiong*, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang

Neural Information Processing Systems (NeurIPS) 2023 Spotlight

Under review in Operations Research (OR)

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Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage

Jose Blanchet, Miao Lu, Tong Zhang, Han Zhong (alphabetical)

Neural Information Processing Systems (NeurIPS) 2023

Major revision in Mathematics of Operations Research (MOR)

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Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes

Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang

International Conference on Learning Representations (ICLR) 2023

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Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy

Zhihan Liu*, Miao Lu*, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang

International Conference on Machine Learning (ICML) 2022

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Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining

Miao Lu*, Xiaolong Luo*, Tianlong Chen, Wuyang Chen, Dong Liu, Zhangyang Wang

International Conference on Learning Representations (ICLR) 2022 Spotlight

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Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization

Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li

Association for the Advancement of Artificial Intelligence (AAAI) 2022

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