Jingwei Li (李经纬)
IIIS, Tsinghua University
Email: ljw22 [at] mails.tsinghua.edu.cn
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Jingwei Li (李经纬) |
I am a PhD student at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University, advised by Professor Jingzhao Zhang. Previously, I received my B.S. degree in Mathematics from Tsinghua University in 2022.
My research lies at the intersection of theoretical and applied machine learning. On the theoretical side, I am interested in establishing provable guarantees for neural network generalization and control theory. On the applied side, my focus is on pre-training data for large language models (LLMs), such as optimizing data mixtures and exploring their effects on model performance.
α–β indicates alphabetical author order, * indicates equal contribution.
Finite Sample Analyses for Continuous-time Linear Systems: System Identification and Online Control [arxiv]
Hongyi Zhou*, Jingwei Li* , Jingzhao Zhang
Conference on Neural Information Processing Systems (NeurIPS) 2025
Towards Black-box Membership Inference Attack for Diffusion Models [arxiv]
Jingwei Li , Jing Dong, Tianxing He, Jingzhao Zhang
International Conference on Machine Learning (ICML) 2025
Understanding Nonlinear Implicit Bias via Region Counts in Input Space [arxiv]
Jingwei Li* , Jing Xu*, Zifan Wang, Huishuai Zhang, Jingzhao Zhang
International Conference on Machine Learning (ICML) 2025
MutualNeRF: Improve the Performance of NeRF under Limited Samples with Mutual Information Theory [arxiv]
Zifan Wang*, Jingwei Li* , Yitang Li, Yunze Liu
International Conference on Uncertainty in Artificial Intelligence (UAI) 2025
Online Control with Adversarial Disturbance for Continuous-time Linear Systems [arxiv]
Jingwei Li , Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang
Conference on Neural Information Processing Systems (NeurIPS) 2024
Online Policy Optimization for Robust Markov Decision Process [arxiv]
(α–β) Jing Dong, Jingwei Li , Baoxiang Wang, Jingzhao Zhang
International Conference on Uncertainty in Artificial Intelligence (UAI) 2024
Iteratively Learn Diverse Strategies with State Distance Information [arxiv]
Wei Fu, Weihua Du* , Jingwei Li* , Sunli Chen, Jingzhao Zhang, Yi Wu
Conference on Neural Information Processing Systems (NeurIPS) 2023
KIMI K2.5: Visual Agentic Intelligence [arxiv]
Kimi Team et al.
Moonshot AI (KIMI)
2025.07 - 2026.02
Algorithm Intern at Pre-training Team
Focused on data mixture and multi-epoch training for large language models (LLM) mid-training. Worked on developing efficient strategies for optimizing data mixture and training epochs. Contributed to the development of KIMI K2.5 pre-training phase.
Microsoft Research Asia (MSRA)
2023.08 - 2023.12
Research Intern at Machine Learning Theory Team
Worked on deep learning theory, specifically on measures to describe implicit bias in neural networks. Successfully achieved a correlation of 0.98 between the generalization gap and the measure, providing insights into how to improve neural network generalization.