| 2026 | ACL | Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization. | Tiancheng Xing, Jerry Li, Yixuan Du, Xiyang Hu |
| 2026 | COLT | Optimal Inference Schedules for Masked Diffusion Models. | Sitan Chen, Kevin Cong, Jerry Li |
| 2026 | COLT | Separating Oblivious and Adaptive Models of Variable Selection (Extended Abstract). | Ziyun Chen, Jerry Li, Kevin Tian, Yusong Zhu |
| 2026 | COLT | Density estimation for Hellinger via minimum-distance estimators: mixtures of Gaussians, log-concave, and more. | Spencer Compton, Jerry Li |
| 2026 | STOC | High-Accuracy List-Decodable Mean Estimation. | Ziyun Chen, Spencer Compton, Daniel M. Kane, Jerry Li |
| 2026 | STOC | The Power of Two Bases: Robust and Copy-Optimal Certification of Nearly All Quantum States with Few-Qubit Measurements. | Andrea Coladangelo, Jerry Li, Joseph Slote, Ellen Wu |
| 2026 | STOC | Rigorous Implications of the Low-Degree Heuristic. | Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel |
| 2025 | COLT | Predicting quantum channels over general product distributions. | Sitan Chen, Jaume de Dios Pont, Jun-Ting Hsieh, Hsin-Yuan Huang, Jane Lange, Jerry Li |
| 2025 | HPDC | Understanding Error Sensitivity in Checkpointing for Linear System Solvers. | Bohan Zhang, Yafan Huang, Jerry Li, Guanpeng Li |
| 2025 | ICML | S4S: Solving for a Fast Diffusion Model Solver. | Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh |
| 2025 | VTC | A Realistic Radar Simulator for End-to-End Autonomous Driving in CARLA. | Satyam Srivastava, Jerry Li, Pushkal Mishra, Kshitiz Bansal, Dinesh Bharadia |
| 2025 | STOC | Learning the Closest Product State. | Ainesh Bakshi, John Bostanci, William Kretschmer, Zeph Landau, Jerry Li, Allen Liu, Ryan O'Donnell, Ewin Tang |
| 2025 | SENSYS | Demo Abstract: C-Shenron: A Realistic Radar Simulation Framework for CARLA. | Pushkal Mishra, Satyam Srivastava, Jerry Li, Kshitiz Bansal, Dinesh Bharadia |
| 2025 | SENSYS | Demo Abstract: Cooperative Multi-modal Sensing. | Bo Wu, Jerry Li, Ruoshen Mo, Justin Yue, Dinesh Bharadia, Hang Qiu |
| 2024 | COLT | Black-Box k-to-1-PCA Reductions: Theory and Applications. | Arun Jambulapati, Syamantak Kumar, Jerry Li, Shourya Pandey, Ankit Pensia, Kevin Tian |
| 2024 | ICLR | KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval. | Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yksekgnl, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi |
| 2024 | STOC | An Optimal Tradeoff between Entanglement and Copy Complexity for State Tomography. | Sitan Chen, Jerry Li, Allen Liu |
| 2023 | COLT | Semi-Random Sparse Recovery in Nearly-Linear Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | EMNLP | Automatic Prompt Optimization with "Gradient Descent" and Beam Search. | Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng |
| 2023 | FOCS | The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination. | Clment L. Canonne, Samuel B. Hopkins, Jerry Li, Allen Liu, Shyam Narayanan |
| 2023 | FOCS | When Does Adaptivity Help for Quantum State Learning? | Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke |
| 2023 | FOCS | Query lower bounds for log-concave sampling. | Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan |
| 2023 | FOCS | Matrix Completion in Almost-Verification Time. | Jonathan A. Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian |
| 2023 | ICCV | REAP: A Large-Scale Realistic Adversarial Patch Benchmark. | Nabeel Hingun, Chawin Sitawarin, Jerry Li, David A. Wagner |
| 2023 | ICLR | Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. | Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang |
| 2023 | STOC | Learning Polynomial Transformations via Generalized Tensor Decompositions. | Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang |
| 2022 | COLT | The Price of Tolerance in Distribution Testing. | Clment L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li |
| 2022 | COLT | Toward Instance-Optimal State Certification With Incoherent Measurements. | Sitan Chen, Jerry Li, Ryan O'Donnell |
| 2022 | FOCS | Tight Bounds for Quantum State Certification with Incoherent Measurements. | Sitan Chen, Jerry Li, Brice Huang, Allen Liu |
| 2022 | ICLR | Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. | Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka |
| 2022 | STOC | Clustering mixture models in almost-linear time via list-decodable mean estimation. | Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian |
| 2022 | STOC | Clustering mixtures with almost optimal separation in polynomial time. | Allen Liu, Jerry Li |
| 2021 | COLT | Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent. | Matthew S. Brennan, Guy Bresler, Samuel B. Hopkins, Jerry Li, Tselil Schramm |
| 2021 | ESA | Finding an Approximate Mode of a Kernel Density Estimate. | Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai |
| 2021 | FOCS | Exponential Separations Between Learning With and Without Quantum Memory. | Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li |
| 2021 | ICLR | Byzantine-Resilient Non-Convex Stochastic Gradient Descent. | Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li, Dan Alistarh |
| 2021 | ICLR | Aligning AI With Shared Human Values. | Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt |
| 2020 | FOCS | Entanglement is Necessary for Optimal Quantum Property Testing. | Sbastien Bubeck, Sitan Chen, Jerry Li |
| 2020 | ICASSP | Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. | Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco |
| 2020 | ICML | Randomized Smoothing of All Shapes and Sizes. | Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li |
| 2020 | SODA | Sample Efficient Toeplitz Covariance Estimation. | Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco |
| 2020 | STOC | Efficiently learning structured distributions from untrusted batches. | Sitan Chen, Jerry Li, Ankur Moitra |
| 2020 | STOC | Learning mixtures of linear regressions in subexponential time via Fourier moments. | Sitan Chen, Jerry Li, Zhao Song |
| 2020 | STOC | Positive semidefinite programming: mixed, parallel, and width-independent. | Arun Jambulapati, Yin Tat Lee, Jerry Li, Swati Padmanabhan, Kevin Tian |
| 2019 | COLT | How Hard is Robust Mean Estimation? | Samuel B. Hopkins, Jerry Li |
| 2019 | COLT | Privately Learning High-Dimensional Distributions. | Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman |
| 2019 | COLT | On Mean Estimation for General Norms with Statistical Queries. | Jerry Li, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten |
| 2019 | ICML | Sever: A Robust Meta-Algorithm for Stochastic Optimization. | Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart |
| 2018 | COLT | Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. | Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2018 | ICML | On the Limitations of First-Order Approximation in GAN Dynamics. | Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt |
| 2018 | SODA | Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. | Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart |
| 2018 | STOC | Mixture models, robustness, and sum of squares proofs. | Samuel B. Hopkins, Jerry Li |
| 2017 | COLT | Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities. | Jerry Li, Ludwig Schmidt |
| 2017 | COLT | Computationally Efficient Robust Sparse Estimation in High Dimensions. | Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh |
| 2017 | ICML | Being Robust (in High Dimensions) Can Be Practical. | Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart |
| 2017 | ICML | ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning. | Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang |
| 2017 | PODC | The Power of Choice in Priority Scheduling. | Dan Alistarh, Justin Kopinsky, Jerry Li, Giorgi Nadiradze |
| 2017 | SODA | Sample-Optimal Density Estimation in Nearly-Linear Time. | Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2016 | CSCW | Designing Shared Gaze Awareness for Remote Collaboration. | Jerry Li, Mia E. Manavalan, Sarah D'Angelo, Darren Gergle |
| 2016 | FOCS | Robust Estimators in High Dimensions without the Computational Intractability. | Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart |
| 2016 | ICML | Fast Algorithms for Segmented Regression. | Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2015 | ICALP | Replacing Mark Bits with Randomness in Fibonacci Heaps. | Jerry Li, John Peebles |
| 2015 | PPoPP | The SprayList: a scalable relaxed priority queue. | Dan Alistarh, Justin Kopinsky, Jerry Li, Nir Shavit |
| 2014 | ICDT | Counting of Query Expressions: Limitations of Propositional Methods. | Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu |
| 2014 | OPODIS | On the Importance of Registers for Computability. | Rati Gelashvili, Mohsen Ghaffari, Jerry Li, Nir Shavit |
| 2013 | UAI | Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases. | Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu |