Me

Welcome!

Hi, I’m Qianli — a Research Scientist at Alibaba Group’s Tongyi Lab. I split my time between research on large language models (LLMs) and building open-source AI infrastructure.

I received my Ph.D. from the School of Computing at the National University of Singapore, advised by Prof. Kenji Kawaguchi. Before that, I earned a B.S. in Computer Science from Peking University, where I worked with Prof. Zhanxing Zhu. I’ve also spent time at Baichuan Inc., Sea AI Lab, and as a visiting researcher at Georgia Tech.

Outside of work, I enjoy 🐱🏀🤿🎿🧑‍🍳🎮🃏 …

Email: shenqianlilili[at]gmail.com

[CV] [Google Scholar] [GitHub] [WeChat]


Selected Publications (* indicates equal contribution)

Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization [arxiv][code]
Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi
In Advances in Neural Information Processing Systems (NeurIPS), 2024

The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline [arxiv][code]
Haonan Wang, Qianli Shen, Yao Tong, Yang Zhang, Kenji Kawaguchi
International Conference on Machine Learning (ICML), 2024 (Oral)

VA3: Virtually Assured Amplification Attack on Probabilistic Copyright Protection for Text-to-Image Generative Models [arxiv][code]
Xiang Li*, Qianli Shen*, Kenji Kawaguchi
Conference on Computer Vision and Pattern Recognition (CVPR), 2024 (Highlight)

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification [arxiv][code]
Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos Psaros, Kenji Kawaguchi
In Advances in Neural Information Processing Systems (NeurIPS), 2023

Deep Reinforcement Learning with Robust and Smooth Policy [arxiv]
Qianli Shen*, Yan Li*, Haoming Jiang, Zhaoran Wang, Tuo Zhao
International Conference on Machine Learning (ICML), 2020


Softwares

PRIMAL: PaRametric sImplex Method for spArse Learning