Jerry Li

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization ACL 2026 Density estimation for Hellinger via minimum-distance estimators: mixtures of Gaussians, log-concave, and more COLT 2026 Optimal Inference Schedules for Masked Diffusion Models COLT 2026 Separating Oblivious and Adaptive Models of Variable Selection (Extended Abstract) COLT 2026 BEVCalib: LiDAR-Camera Calibration via Geometry-Guided Bird’s-Eye View Representation CoRL 2025 Predicting quantum channels over general product distributions COLT 2025 S4S: Solving for a Fast Diffusion Model Solver ICML 2025 Black-Box k-to-1-PCA Reductions: Theory and Applications COLT 2024 KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval ICLR 2024 Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting NeurIPS 2024 Automatic Prompt Optimization with “Gradient Descent” and Beam Search EMNLP 2023 REAP: A Large-Scale Realistic Adversarial Patch Benchmark ICCV 2023 Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions ICLR 2023 Semi-Random Sparse Recovery in Nearly-Linear Time COLT 2023 Structured Semidefinite Programming for Recovering Structured Preconditioners NeurIPS 2023 Learning (Very) Simple Generative Models Is Hard NeurIPS 2022 Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs ICLR 2022 Robust Model Selection and Nearly-Proper Learning for GMMs NeurIPS 2022 The Price of Tolerance in Distribution Testing COLT 2022 Toward Instance-Optimal State Certification With Incoherent Measurements COLT 2022 Aligning AI With Shared Human Values ICLR 2021 Byzantine-Resilient Non-Convex Stochastic Gradient Descent ICLR 2021 List-Decodable Mean Estimation in Nearly-PCA Time NeurIPS 2021 Robust Regression Revisited: Acceleration and Improved Estimation Rates NeurIPS 2021 Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent COLT 2021 Learning Structured Distributions From Untrusted Batches: Faster and Simpler NeurIPS 2020 Randomized Smoothing of All Shapes and Sizes ICML 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning NeurIPS 2020 Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization NeurIPS 2020 Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time NeurIPS 2020 Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing NeurIPS 2020 How Hard is Robust Mean Estimation? COLT 2019 On Mean Estimation for General Norms with Statistical Queries COLT 2019 Privately Learning High-Dimensional Distributions COLT 2019 Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers NeurIPS 2019 Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection NeurIPS 2019 Sever: A Robust Meta-Algorithm for Stochastic Optimization ICML 2019 Byzantine Stochastic Gradient Descent NeurIPS 2018 Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms COLT 2018 On the Limitations of First-Order Approximation in GAN Dynamics ICML 2018 Spectral Signatures in Backdoor Attacks NeurIPS 2018 Being Robust (in High Dimensions) Can Be Practical ICML 2017 Communication-Efficient Distributed Learning of Discrete Distributions NeurIPS 2017 Computationally Efficient Robust Sparse Estimation in High Dimensions COLT 2017 QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NeurIPS 2017 Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities COLT 2017 ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning ICML 2017 Fast Algorithms for Segmented Regression ICML 2016