Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift. - Jeremy Z. Kolter; Marcus A. Maloof (ICDM, 2003)

Learning to detect malicious executables in the wild. - Jeremy Z. Kolter; Marcus A. Maloof (KDD, 2004)

Using additive expert ensembles to cope with concept drift. - Jeremy Z. Kolter; Marcus A. Maloof (ICML, 2005)

Learning to Detect and Classify Malicious Executables in the Wild. - Jeremy Z. Kolter; Marcus A. Maloof (J. Mach. Learn. Res., 2006)

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion. - J. Zico Kolter; Pieter Abbeel; Andrew Y. Ng (NIPS, 2007)

Learning omnidirectional path following using dimensionality reduction. - J. Zico Kolter; Andrew Y. Ng (Robotics: Science and Systems, 2007)

Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts. - J. Zico Kolter; Marcus A. Maloof (J. Mach. Learn. Res., 2007)

Space-indexed dynamic programming: learning to follow trajectories. - J. Zico Kolter; Adam Coates 002; Andrew Y. Ng; Yi Gu; Charles DuHadway (ICML, 2008)

A control architecture for quadruped locomotion over rough terrain. - J. Zico Kolter; Mike P. Rodgers; Andrew Y. Ng (ICRA, 2008)

Near-Bayesian exploration in polynomial time. - J. Zico Kolter; Andrew Y. Ng (ICML, 2009)

Regularization and feature selection in least-squares temporal difference learning. - J. Zico Kolter; Andrew Y. Ng (ICML, 2009)

Stereo vision and terrain modeling for quadruped robots. - J. Zico Kolter; Youngjun Kim; Andrew Y. Ng (ICRA, 2009)

Task-space trajectories via cubic spline optimization. - J. Zico Kolter; Andrew Y. Ng (ICRA, 2009)

Policy search via the signed derivative. - J. Zico Kolter; Andrew Y. Ng (Robotics: Science and Systems, 2009)

A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving. - J. Zico Kolter; Christian Plagemann; David T. Jackson; Andrew Y. Ng; Sebastian Thrun (ICRA, 2010)

Energy Disaggregation via Discriminative Sparse Coding. - J. Zico Kolter; Siddharth Batra; Andrew Y. Ng (NIPS, 2010)

Learning and control with inaccurate models. - J. Zico Kolter (2010)

A Large-Scale Study on Predicting and Contextualizing Building Energy Usage. - J. Zico Kolter; Joseph Ferreira Jr. (AAAI, 2011)

Towards fully autonomous driving: Systems and algorithms. - Jesse Levinson; Jake Askeland; Jan Becker; Jennifer Dolson; David Held; Sören Kammel; J. Zico Kolter; Dirk Langer; Oliver Pink; Vaughan R. Pratt; Michael Sokolsky; Ganymed Stanek; et al. (Intelligent Vehicles Symposium, 2011)

The Fixed Points of Off-Policy TD. - J. Zico Kolter (NIPS, 2011)

The Stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion. - J. Zico Kolter; Andrew Y. Ng (Int. J. Robotics Res., 2011)

Design, analysis, and learning control of a fully actuated micro wind turbine. - J. Zico Kolter; Zachary Jackowski; Russ Tedrake (ACC, 2012)

Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation. - J. Zico Kolter; Tommi S. Jaakkola (AISTATS, 2012)

Large-scale probabilistic forecasting in energy systems using sparse Gaussian conditional random fields. - Matt Wytock; J. Zico Kolter (CDC, 2013)

Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting. - Matt Wytock; J. Zico Kolter (ICML (3), 2013)

A moving horizon state estimator in the control of thermostatically controlled loads for demand response. - Emre Can Kara; J. Zico Kolter; Mario Berges; Bruce H. Krogh; Gabriela Hug; Tugçe Yüksel (SmartGridComm, 2013)

A Fast Algorithm for Sparse Controller Design. - Matt Wytock; J. Zico Kolter (CoRR, 2013)

Contextually Supervised Source Separation with Application to Energy Disaggregation. - Matt Wytock; J. Zico Kolter (AAAI, 2014)

Fast Newton methods for the group fused lasso. - Matt Wytock; Suvrit Sra; Jeremy Z. Kolter (UAI, 2014)

An Additive Autoregressive Hidden Markov Model for Energy Disaggregation. - Kirstin Early; J. Zico Kolter (AAAI Workshop: Computational Sustainability, 2015)

An SVD and Derivative Kernel Approach to Learning from Geometric Data. - Eric Wong 001; J. Zico Kolter (AAAI, 2015)

Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization. - Alnur Ali; J. Zico Kolter; Steven Diamond; Stephen P. Boyd (UAI, 2015)

Optimal Planning and Learning in Uncertain Environments for the Management of Wind Farms. - Milad Memarzadeh; Matteo Pozzi; J. Zico Kolter (J. Comput. Civ. Eng., 2015)

Epigraph projections for fast general convex programming. - Po-Wei Wang; Matt Wytock; J. Zico Kolter (ICML, 2016)

The Multiple Quantile Graphical Model. - Alnur Ali; J. Zico Kolter; Ryan J. Tibshirani (NIPS, 2016)

Computational approaches for efficient scheduling of steel plants as demand response resource. - Xiao Zhang 005; Gabriela Hug; J. Zico Kolter; Iiro Harjunkoski (PSCC, 2016)

Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control. - Milad Memarzadeh; Matteo Pozzi; J. Zico Kolter (Reliab. Eng. Syst. Saf., 2016)

Polynomial Optimization Methods for Matrix Factorization. - Po-Wei Wang; Chun-Liang Li; J. Zico Kolter (AAAI, 2017)

A Semismooth Newton Method for Fast, Generic Convex Programming. - Alnur Ali; Eric Wong 001; J. Zico Kolter (ICML, 2017)

OptNet: Differentiable Optimization as a Layer in Neural Networks. - Brandon Amos; J. Zico Kolter (ICML, 2017)

Input Convex Neural Networks. - Brandon Amos; Lei Xu 040; J. Zico Kolter (ICML, 2017)

Task-based End-to-end Model Learning in Stochastic Optimization. - Priya L. Donti; J. Zico Kolter; Brandon Amos (NIPS, 2017)

Gradient descent GAN optimization is locally stable. - Vaishnavh Nagarajan; J. Zico Kolter (NIPS, 2017)

Task-based End-to-end Model Learning. - Priya L. Donti; Brandon Amos; J. Zico Kolter (CoRR, 2017)

The Mixing method: coordinate descent for low-rank semidefinite programming. - Po-Wei Wang; Wei-Cheng Chang; J. Zico Kolter (CoRR, 2017)

Intelligent Pothole Detection and Road Condition Assessment. - Umang Bhatt; Shouvik Mani; Edgar Xi; J. Zico Kolter (CoRR, 2017)

Convolutional Sequence Modeling Revisited. - Shaojie Bai; J. Zico Kolter; Vladlen Koltun (ICLR (Workshop), 2018)

Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope. - Eric Wong 001; J. Zico Kolter (ICML, 2018)

What Game Are We Playing? End-to-end Learning in Normal and Extensive Form Games. - Chun Kai Ling; Fei Fang 001; J. Zico Kolter (IJCAI, 2018)

Differentiable MPC for End-to-end Planning and Control. - Brandon Amos; Ivan Dario Jimenez Rodriguez; Jacob Sacks; Byron Boots; J. Zico Kolter (NeurIPS, 2018)

End-to-End Differentiable Physics for Learning and Control. - Filipe de Avila Belbute-Peres; Kevin A. Smith 001; Kelsey R. Allen; Josh Tenenbaum 001; J. Zico Kolter (NeurIPS, 2018)

Scaling provable adversarial defenses. - Eric Wong 001; Frank R. Schmidt; Jan Hendrik Metzen; J. Zico Kolter (NeurIPS, 2018)

Realtime Query Completion via Deep Language Models. - Po-Wei Wang; Huan Zhang 001; Vijai Mohan; Inderjit S. Dhillon; J. Zico Kolter (eCOM@SIGIR, 2018)

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. - Shaojie Bai; J. Zico Kolter; Vladlen Koltun (CoRR, 2018)

Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games. - Chun Kai Ling; Fei Fang 001; J. Zico Kolter (AAAI, 2019)

Low-Rank Semidefinite Programming for the MAX2SAT Problem. - Po-Wei Wang; J. Zico Kolter (AAAI, 2019)

Multimodal Transformer for Unaligned Multimodal Language Sequences. - Yao-Hung Hubert Tsai; Shaojie Bai; Paul Pu Liang; J. Zico Kolter; Louis-Philippe Morency; Ruslan Salakhutdinov (ACL (1), 2019)

A Continuous-Time View of Early Stopping for Least Squares Regression. - Alnur Ali; J. Zico Kolter; Ryan J. Tibshirani (AISTATS, 2019)

Neural Variational Identification and Filtering for Stochastic Non-linear Dynamical Systems with Application to Non-intrusive Load Monitoring. - Henning Lange; Mario Bergés; J. Zico Kolter (ICASSP, 2019)

Trellis Networks for Sequence Modeling. - Shaojie Bai; J. Zico Kolter; Vladlen Koltun (ICLR (Poster), 2019)

Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience. - Vaishnavh Nagarajan; J. Zico Kolter (ICLR (Poster), 2019)

Certified Adversarial Robustness via Randomized Smoothing. - Jeremy Cohen 001; Elan Rosenfeld; J. Zico Kolter (ICML, 2019)

Adversarial camera stickers: A physical camera-based attack on deep learning systems. - Juncheng Li 001; Frank R. Schmidt; J. Zico Kolter (ICML, 2019)

SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. - Po-Wei Wang; Priya L. Donti; Bryan Wilder; J. Zico Kolter (ICML, 2019)

Wasserstein Adversarial Examples via Projected Sinkhorn Iterations. - Eric Wong 001; Frank R. Schmidt; J. Zico Kolter (ICML, 2019)

Adversarial Music: Real world Audio Adversary against Wake-word Detection System. - Juncheng Li 001; Shuhui Qu; Xinjian Li; Joseph Szurley; J. Zico Kolter; Florian Metze (NeurIPS, 2019)

Differentiable Convex Optimization Layers. - Akshay Agrawal 001; Brandon Amos; Shane T. Barratt; Stephen P. Boyd; Steven Diamond; J. Zico Kolter (NeurIPS, 2019)

Deep Equilibrium Models. - Shaojie Bai; J. Zico Kolter; Vladlen Koltun (NeurIPS, 2019)

Learning Stable Deep Dynamics Models. - J. Zico Kolter; Gaurav Manek (NeurIPS, 2019)

Uniform convergence may be unable to explain generalization in deep learning. - Vaishnavh Nagarajan; J. Zico Kolter (NeurIPS, 2019)

Computational sustainability: computing for a better world and a sustainable future. - Carla P. Gomes; Thomas G. Dietterich; Christopher Barrett; Jon Conrad; Bistra Dilkina; Stefano Ermon; Fei Fang 001; Andrew Farnsworth; Alan Fern; Xiaoli Z. Fern; Daniel Fink 002; Douglas H. Fisher; et al. (Commun. ACM, 2019)

Generalization in Deep Networks: The Role of Distance from Initialization. - Vaishnavh Nagarajan; J. Zico Kolter (CoRR, 2019)

Perceptual Based Adversarial Audio Attacks. - Joseph Szurley; J. Zico Kolter (CoRR, 2019)

The Limited Multi-Label Projection Layer. - Brandon Amos; Vladlen Koltun; J. Zico Kolter (CoRR, 2019)

On Physical Adversarial Patches for Object Detection. - Mark Lee; J. Zico Kolter (CoRR, 2019)

Black-box Adversarial Attacks with Bayesian Optimization. - Satya Narayan Shukla; Anit Kumar Sahu; Devin Willmott; J. Zico Kolter (CoRR, 2019)

Adversarial Music: Real World Audio Adversary Against Wake-word Detection System. - Juncheng B. Li; Shuhui Qu; Xinjian Li; J. Zico Kolter; Florian Metze (CoRR, 2019)

Dynamic Modeling and Equilibria in Fair Decision Making. - Joshua Williams 001; J. Zico Kolter (CoRR, 2019)

AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning. - Rizal Fathony; J. Zico Kolter (AISTATS, 2020)

A Framework for robustness Certification of Smoothed Classifiers using F-Divergences. - Krishnamurthy (Dj) Dvijotham; Jamie Hayes; Borja Balle; J. Zico Kolter; Chongli Qin; András György 001; Kai Xiao; Sven Gowal; Pushmeet Kohli (ICLR, 2020)

Differentiable learning of numerical rules in knowledge graphs. - Po-Wei Wang; Daria Stepanova 001; Csaba Domokos; J. Zico Kolter (ICLR, 2020)

Fast is better than free: Revisiting adversarial training. - Eric Wong 001; Leslie Rice; J. Zico Kolter (ICLR, 2020)

Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction. - Filipe de Avila Belbute-Peres; Thomas D. Economon; J. Zico Kolter (ICML, 2020)

Adversarial Robustness Against the Union of Multiple Perturbation Models. - Pratyush Maini; Eric Wong 001; J. Zico Kolter (ICML, 2020)

Overfitting in adversarially robust deep learning. - Leslie Rice; Eric Wong 001; J. Zico Kolter (ICML, 2020)

Certified Robustness to Label-Flipping Attacks via Randomized Smoothing. - Elan Rosenfeld; Ezra Winston; Pradeep Ravikumar; J. Zico Kolter (ICML, 2020)

Neural Network Virtual Sensors for Fuel Injection Quantities with Provable Performance Specifications. - Eric Wong 001; Tim Schneider; Joerg Schmitt; Frank R. Schmidt; J. Zico Kolter (IV, 2020)

Multiscale Deep Equilibrium Models. - Shaojie Bai; Vladlen Koltun; J. Zico Kolter (NeurIPS, 2020)

Deep Archimedean Copulas. - Chun Kai Ling; Fei Fang 001; J. Zico Kolter (NeurIPS, 2020)

Efficient semidefinite-programming-based inference for binary and multi-class MRFs. - Chirag Pabbaraju; Po-Wei Wang; J. Zico Kolter (NeurIPS, 2020)

Denoised Smoothing: A Provable Defense for Pretrained Classifiers. - Hadi Salman; Mingjie Sun; Greg Yang; Ashish Kapoor; J. Zico Kolter (NeurIPS, 2020)

Community detection using fast low-cardinality semidefinite programming . - Po-Wei Wang; J. Zico Kolter (NeurIPS, 2020)

Monotone operator equilibrium networks. - Ezra Winston; J. Zico Kolter (NeurIPS, 2020)

Black-box Smoothing: A Provable Defense for Pretrained Classifiers. - Hadi Salman; Mingjie Sun; Greg Yang; Ashish Kapoor; J. Zico Kolter (CoRR, 2020)

Provably robust deep generative models. - Filipe Condessa; J. Zico Kolter (CoRR, 2020)

Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. - Satya Narayan Shukla; Anit Kumar Sahu; Devin Willmott; J. Zico Kolter (CoRR, 2020)

A community-powered search of machine learning strategy space to find NMR property prediction models. - Lars A. Bratholm; Will Gerrard; Brandon M. Anderson; Shaojie Bai; Sunghwan Choi; Lam Dang; Pavel Hanchar; Addison Howard; Guillaume Huard; Sanghoon Kim; J. Zico Kolter; Risi Kondor; et al. (CoRR, 2020)

Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks. - Anit Kumar Sahu; Satya Narayan Shukla; J. Zico Kolter (CoRR, 2020)

Poisoned classifiers are not only backdoored, they are fundamentally broken. - Mingjie Sun; Siddhant Agarwal; J. Zico Kolter (CoRR, 2020)

Challenging common interpretability assumptions in feature attribution explanations. - Jonathan Dinu; Jeffrey P. Bigham; J. Zico Kolter (CoRR, 2020)

Provably Safe PAC-MDP Exploration Using Analogies. - Melrose Roderick; Vaishnavh Nagarajan; J. Zico Kolter (AISTATS, 2021)

Defending Multimodal Fusion Models Against Single-Source Adversaries. - Karren Yang; Wan-Yi Lin; Manash Barman; Filipe Condessa; J. Zico Kolter (CVPR, 2021)

Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits. - Leonid Boytsov; Zico Kolter (ECIR (1), 2021)

Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization. - Bingqing Chen; Priya L. Donti; Kyri Baker; J. Zico Kolter; Mario Bergés (e-Energy, 2021)

A Bayesian Model of Cash Bail Decisions. - Joshua Williams 001; J. Zico Kolter (FAccT, 2021)

Learning perturbation sets for robust machine learning. - Eric Wong 001; J. Zico Kolter (ICLR, 2021)

Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability. - Jeremy Cohen 001; Simran Kaur 001; Yuanzhi Li; J. Zico Kolter; Ameet Talwalkar (ICLR, 2021)

Enforcing robust control guarantees within neural network policies. - Priya L. Donti; Melrose Roderick; Mahyar Fazlyab; J. Zico Kolter (ICLR, 2021)

DC3: A learning method for optimization with hard constraints. - Priya L. Donti; David Rolnick; J. Zico Kolter (ICLR, 2021)

Multiplicative Filter Networks. - Rizal Fathony; Anit Kumar Sahu; Devin Willmott; J. Zico Kolter (ICLR, 2021)

Estimating Lipschitz constants of monotone deep equilibrium models. - Chirag Pabbaraju; Ezra Winston; J. Zico Kolter (ICLR, 2021)

Provably robust classification of adversarial examples with detection. - Fatemeh Sheikholeslami; Ali Lotfi; J. Zico Kolter (ICLR, 2021)

Orthogonalizing Convolutional Layers with the Cayley Transform. - Asher Trockman; J. Zico Kolter (ICLR, 2021)

Stabilizing Equilibrium Models by Jacobian Regularization. - Shaojie Bai; Vladlen Koltun; J. Zico Kolter (ICML, 2021)

RATT: Leveraging Unlabeled Data to Guarantee Generalization. - Saurabh Garg; Sivaraman Balakrishnan; J. Zico Kolter; Zachary C. Lipton (ICML, 2021)

On Proximal Policy Optimization's Heavy-tailed Gradients. - Saurabh Garg; Joshua Zhanson; Emilio Parisotto; Adarsh Prasad; J. Zico Kolter; Zachary C. Lipton; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Pradeep Ravikumar (ICML, 2021)

DORO: Distributional and Outlier Robust Optimization. - Runtian Zhai; Chen Dan 001; J. Zico Kolter; Pradeep Ravikumar (ICML, 2021)

Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. - Satya Narayan Shukla; Anit Kumar Sahu; Devin Willmott; J. Zico Kolter (KDD, 2021)

Adversarially robust learning for security-constrained optimal power flow. - Priya L. Donti; Aayushya Agarwal; Neeraj Vijay Bedmutha; Larry T. Pileggi; J. Zico Kolter (NeurIPS, 2021)

Joint inference and input optimization in equilibrium networks. - Swaminathan Gurumurthy; Shaojie Bai; Zachary Manchester; J. Zico Kolter (NeurIPS, 2021)

$( textrm{Implicit})^2$: Implicit Layers for Implicit Representations. - Zhichun Huang; Shaojie Bai; J. Zico Kolter (NeurIPS, 2021)

Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds. - Yujia Huang; Huan Zhang 001; Yuanyuan Shi; J. Zico Kolter; Anima Anandkumar (NeurIPS, 2021)

Robustness between the worst and average case. - Leslie Rice; Anna Bair; Huan Zhang 001; J. Zico Kolter (NeurIPS, 2021)

Monte Carlo Tree Search With Iteratively Refining State Abstractions. - Samuel Sokota; Caleb Ho; Zaheen Farraz Ahmad; J. Zico Kolter (NeurIPS, 2021)

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification. - Shiqi Wang 002; Huan Zhang 001; Kaidi Xu; Xue Lin 001; Suman Jana; Cho-Jui Hsieh; J. Zico Kolter (NeurIPS, 2021)

Boosted CVaR Classification. - Runtian Zhai; Chen Dan 001; Arun Sai Suggala; J. Zico Kolter; Pradeep Ravikumar (NeurIPS, 2021)

You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries. - Devin Willmott; Anit Kumar Sahu; Fatemeh Sheikholeslami; Filipe Condessa; J. Zico Kolter (CoRR, 2021)

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Verification. - Shiqi Wang 002; Huan Zhang 001; Kaidi Xu; Xue Lin 001; Suman Jana; Cho-Jui Hsieh; J. Zico Kolter (CoRR, 2021)

DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting. - Shaoru Chen; Eric Wong 001; J. Zico Kolter; Mahyar Fazlyab (CoRR, 2021)

Deep Equilibrium Optical Flow Estimation. - Shaojie Bai; Zhengyang Geng; Yash Savani; J. Zico Kolter (CVPR, 2022)

Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation. - Nadine Behrmann; S. Alireza Golestaneh; Zico Kolter; Jürgen Gall; Mehdi Noroozi (ECCV (35), 2022)

Neural Deep Equilibrium Solvers. - Shaojie Bai; Vladlen Koltun; J. Zico Kolter (ICLR, 2022)

Assessing Generalization of SGD via Disagreement. - Yiding Jiang; Vaishnavh Nagarajan; Christina Baek; J. Zico Kolter (ICLR, 2022)

A Fine-Tuning Approach to Belief State Modeling. - Samuel Sokota; Hengyuan Hu; David J. Wu 002; J. Zico Kolter; Jakob Nicolaus Foerster; Noam Brown (ICLR, 2022)

Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation. - Colin Wei; J. Zico Kolter (ICLR, 2022)

Communicating via Markov Decision Processes. - Samuel Sokota; Christian A. Schröder de Witt; Maximilian Igl; Luisa M. Zintgraf; Philip H. S. Torr; Martin Strohmeier; J. Zico Kolter; Shimon Whiteson; Jakob N. Foerster (ICML, 2022)

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks. - Huan Zhang 001; Shiqi Wang 002; Kaidi Xu; Yihan Wang; Suman Jana; Cho-Jui Hsieh; J. Zico Kolter (ICML, 2022)

Path Independent Equilibrium Models Can Better Exploit Test-Time Computation. - Cem Anil; Ashwini Pokle; Kaiqu Liang; Johannes Treutlein; Yuhuai Wu; Shaojie Bai; J. Zico Kolter; Roger B. Grosse (NeurIPS, 2022)

Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift. - Christina Baek; Yiding Jiang; Aditi Raghunathan; J. Zico Kolter (NeurIPS, 2022)

Test Time Adaptation via Conjugate Pseudo-labels. - Sachin Goyal; Mingjie Sun; Aditi Raghunathan; J. Zico Kolter (NeurIPS, 2022)

Learning Options via Compression. - Yiding Jiang; Evan Zheran Liu; Benjamin Eysenbach; J. Zico Kolter; Chelsea Finn (NeurIPS, 2022)

Characterizing Datapoints via Second-Split Forgetting. - Pratyush Maini; Saurabh Garg; Zachary C. Lipton; J. Zico Kolter (NeurIPS, 2022)

The Pitfalls of Regularization in Off-Policy TD Learning. - Gaurav Manek; J. Zico Kolter (NeurIPS, 2022)

Deep Equilibrium Approaches to Diffusion Models. - Ashwini Pokle; Zhengyang Geng; J. Zico Kolter (NeurIPS, 2022)

Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation. - Zhouxing Shi; Yihan Wang; Huan Zhang 001; J. Zico Kolter; Cho-Jui Hsieh (NeurIPS, 2022)

General Cutting Planes for Bound-Propagation-Based Neural Network Verification. - Huan Zhang 001; Shiqi Wang 002; Kaidi Xu; Linyi Li 001; Bo Li 026; Suman Jana; Cho-Jui Hsieh; J. Zico Kolter (NeurIPS, 2022)

Dojo: A Differentiable Simulator for Robotics. - Taylor A. Howell; Simon Le Cleac'h; J. Zico Kolter; Mac Schwager; Zachary Manchester (CoRR, 2022)

Smooth-Reduce: Leveraging Patches for Improved Certified Robustness. - Ameya Joshi; Minh Pham 005; Minsu Cho; Leonid Boytsov; Filipe Condessa; J. Zico Kolter; Chinmay Hegde (CoRR, 2022)

(Certified!!) Adversarial Robustness for Free! - Nicholas Carlini; Florian Tramèr; Krishnamurthy Dvijotham; J. Zico Kolter (CoRR, 2022)

Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games. - Chun Kai Ling; J. Zico Kolter; Fei Fang 001 (AAAI, 2023)

Losses over Labels: Weakly Supervised Learning via Direct Loss Construction. - Dylan Sam; J. Zico Kolter (AAAI, 2023)

Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes. - Sina Baharlouei; Fatemeh Sheikholeslami; Meisam Razaviyayn; Zico Kolter (AISTATS, 2023)

Finetune like you pretrain: Improved finetuning of zero-shot vision models. - Sachin Goyal; Ananya Kumar; Sankalp Garg; Zico Kolter; Aditi Raghunathan (CVPR, 2023)

Single Image Backdoor Inversion via Robust Smoothed Classifiers. - Mingjie Sun; Zico Kolter (CVPR, 2023)

Model-tuning Via Prompts Makes NLP Models Adversarially Robust. - Mrigank Raman; Pratyush Maini; J. Zico Kolter; Zachary C. Lipton; Danish Pruthi (EMNLP, 2023)

Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth. - Filipe de Avila Belbute-Peres; J. Zico Kolter (ICLR, 2023)

(Certified!!) Adversarial Robustness for Free! - Nicholas Carlini; Florian Tramèr; Krishnamurthy (Dj) Dvijotham; Leslie Rice; Mingjie Sun; J. Zico Kolter (ICLR, 2023)

A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games. - Samuel Sokota; Ryan D'Orazio; J. Zico Kolter; Nicolas Loizou; Marc Lanctot; Ioannis Mitliagkas; Noam Brown; Christian Kroer (ICLR, 2023)

Understanding the Covariance Structure of Convolutional Filters. - Asher Trockman; Devin Willmott; J. Zico Kolter (ICLR, 2023)

Perfectly Secure Steganography Using Minimum Entropy Coupling. - Christian Schröder de Witt; Samuel Sokota; J. Zico Kolter; Jakob Nicolaus Foerster; Martin Strohmeier (ICLR, 2023)

Understanding Why Generalized Reweighting Does Not Improve Over ERM. - Runtian Zhai; Chen Dan 001; J. Zico Kolter; Pradeep Kumar Ravikumar (ICLR, 2023)

Can Neural Network Memorization Be Localized? - Pratyush Maini; Michael Curtis Mozer; Hanie Sedghi; Zachary Chase Lipton; J. Zico Kolter; Chiyuan Zhang (ICML, 2023)

Abstracting Imperfect Information Away from Two-Player Zero-Sum Games. - Samuel Sokota; Ryan D'Orazio; Chun Kai Ling; David J. Wu 002; J. Zico Kolter; Noam Brown (ICML, 2023)

Mimetic Initialization of Self-Attention Layers. - Asher Trockman; J. Zico Kolter (ICML, 2023)

Deep Off-Policy Iterative Learning Control. - Swaminathan Gurumurthy; J. Zico Kolter; Zachary Manchester (L4DC, 2023)

Practical Critic Gradient based Actor Critic for On-Policy Reinforcement Learning. - Swaminathan Gurumurthy; Zachary Manchester; J. Zico Kolter (L4DC, 2023)

One-Step Diffusion Distillation via Deep Equilibrium Models. - Zhengyang Geng; Ashwini Pokle; J. Zico Kolter (NeurIPS, 2023)

On the Importance of Exploration for Generalization in Reinforcement Learning. - Yiding Jiang; J. Zico Kolter; Roberta Raileanu (NeurIPS, 2023)

Provably Bounding Neural Network Preimages. - Suhas Kotha; Christopher Brix; J. Zico Kolter; Krishnamurthy Dvijotham; Huan Zhang 001 (NeurIPS, 2023)

Language Models are Weak Learners. - Hariharan Manikandan; Yiding Jiang; J. Zico Kolter (NeurIPS, 2023)

Deep Equilibrium Based Neural Operators for Steady-State PDEs. - Tanya Marwah; Ashwini Pokle; J. Zico Kolter; Zachary C. Lipton; Jianfeng Lu 001; Andrej Risteski (NeurIPS, 2023)

Learning with Explanation Constraints. - Rattana Pukdee; Dylan Sam; J. Zico Kolter; Maria-Florina Balcan; Pradeep Ravikumar (NeurIPS, 2023)

Permutation Equivariant Neural Functionals. - Allan Zhou; Kaien Yang; Kaylee Burns; Adriano Cardace; Yiding Jiang; Samuel Sokota; J. Zico Kolter; Chelsea Finn (NeurIPS, 2023)

Neural Functional Transformers. - Allan Zhou; Kaien Yang; Yiding Jiang; Kaylee Burns; Winnie Xu; Samuel Sokota; J. Zico Kolter; Chelsea Finn (NeurIPS, 2023)

Adversarial robustness in discontinuous spaces via alternating sampling & descent. - Rahul Mysore Venkatesh; Eric Wong 001; Zico Kolter (WACV, 2023)

Permutation Equivariant Neural Functionals. - Allan Zhou; Kaien Yang; Kaylee Burns; Yiding Jiang; Samuel Sokota; J. Zico Kolter; Chelsea Finn (CoRR, 2023)

Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport. - Mukul Bhutani; J. Zico Kolter (CoRR, 2023)

Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single. - Paul Vicol; Zico Kolter; Kevin Swersky (CoRR, 2023)

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation. - Runtian Zhai; Bingbin Liu; Andrej Risteski; Zico Kolter; Pradeep Ravikumar (CoRR, 2023)

Localized Text-to-Image Generation for Free via Cross Attention Control. - Yutong He; Ruslan Salakhutdinov; J. Zico Kolter (CoRR, 2023)

Leveraging Multiple Descriptive Features for Robust Few-shot Image Learning. - Zhili Feng; Anna Bair; J. Zico Kolter (CoRR, 2023)

Importance of equivariant and invariant symmetries for fluid flow modeling. - Varun Shankar; Shivam Barwey; Zico Kolter; Romit Maulik; Venkatasubramanian Viswanathan (CoRR, 2023)

Universal and Transferable Adversarial Attacks on Aligned Language Models. - Andy Zou; Zifan Wang 001; J. Zico Kolter; Matt Fredrikson (CoRR, 2023)

Representation Engineering: A Top-Down Approach to AI Transparency. - Andy Zou; Long Phan; Sarah Li Chen; James Campbell; Phillip Guo; Richard Ren; Alexander Pan; Xuwang Yin; Mantas Mazeika; Ann-Kathrin Dombrowski; Shashwat Goel; Nathaniel Li; et al. (CoRR, 2023)

Reliable Test-Time Adaptation via Agreement-on-the-Line. - Eungyeup Kim; Mingjie Sun; Aditi Raghunathan; Zico Kolter (CoRR, 2023)

On the Neural Tangent Kernel of Equilibrium Models. - Zhili Feng; J. Zico Kolter (CoRR, 2023)

TorchDEQ: A Library for Deep Equilibrium Models. - Zhengyang Geng; J. Zico Kolter (CoRR, 2023)

Projected Off-Policy Q-Learning (POP-QL) for Stabilizing Offline Reinforcement Learning. - Melrose Roderick; Gaurav Manek; Felix Berkenkamp; J. Zico Kolter (CoRR, 2023)

Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation. - Melrose Roderick; Felix Berkenkamp; Fatemeh Sheikholeslami; Zico Kolter (CoRR, 2023)

Monotone deep Boltzmann machines. - Zhili Feng; Ezra Winston; J. Zico Kolter (Trans. Mach. Learn. Res., 2023)

Patches Are All You Need? - Asher Trockman; J. Zico Kolter (Trans. Mach. Learn. Res., 2023)

Scaling Laws for Data Filtering - Data Curation Cannot be Compute Agnostic. - Sachin Goyal; Pratyush Maini; Zachary C. Lipton; Aditi Raghunathan; J. Zico Kolter (CVPR, 2024)

From Variance to Veracity: Unbundling and Mitigating Gradient Variance in Differentiable Bundle Adjustment Layers. - Swaminathan Gurumurthy; Karnik Ram; Bingqing Chen; Zachary Manchester; Zico Kolter (CVPR, 2024)

DART: Implicit Doppler Tomography for Radar Novel View Synthesis. - Tianshu Huang; John Miller 002; Akarsh Prabhakara; Tao Jin; Tarana Laroia; Zico Kolter; Anthony Rowe 001 (CVPR, 2024)

Understanding prompt engineering may not require rethinking generalization. - Victor Akinwande; Yiding Jiang; Dylan Sam; J. Zico Kolter (ICLR, 2024)

Why is SAM Robust to Label Noise? - Christina Baek; J. Zico Kolter; Aditi Raghunathan (ICLR, 2024)

Manifold Preserving Guided Diffusion. - Yutong He; Naoki Murata; Chieh-Hsin Lai; Yuhta Takida; Toshimitsu Uesaka; Dongjun Kim; Wei-Hsiang Liao 001; Yuki Mitsufuji; J. Zico Kolter; Ruslan Salakhutdinov; Stefano Ermon (ICLR, 2024)

On the Joint Interaction of Models, Data, and Features. - Yiding Jiang; Christina Baek; J. Zico Kolter (ICLR, 2024)

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. - Pratyush Maini; Sachin Goyal; Zachary Chase Lipton; J. Zico Kolter; Aditi Raghunathan (ICLR, 2024)

The Update-Equivalence Framework for Decision-Time Planning. - Samuel Sokota; Gabriele Farina; David J. Wu 002; Hengyuan Hu; Kevin A. Wang; J. Zico Kolter; Noam Brown (ICLR, 2024)

A Simple and Effective Pruning Approach for Large Language Models. - Mingjie Sun; Zhuang Liu 003; Anna Bair; J. Zico Kolter (ICLR, 2024)

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression. - Runtian Zhai; Bingbin Liu; Andrej Risteski; J. Zico Kolter; Pradeep Kumar Ravikumar (ICLR, 2024)

Understanding Hallucinations in Diffusion Models through Mode Interpolation. - Sumukh K. Aithal; Pratyush Maini; Zachary C. Lipton; J. Zico Kolter (NeurIPS, 2024)

Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. - Aviv Bick; Kevin Y. Li; Eric P. Xing; J. Zico Kolter; Albert Gu (NeurIPS, 2024)

Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line. - Eungyeup Kim; Mingjie Sun; Christina Baek; Aditi Raghunathan; J. Zico Kolter (NeurIPS, 2024)

One-Step Diffusion Distillation through Score Implicit Matching. - Weijian Luo; Zemin Huang; Zhengyang Geng; J. Zico Kolter; Guo-Jun Qi (NeurIPS, 2024)

Diffusing Differentiable Representations. - Yash Savani; Marc Finzi; J. Zico Kolter (NeurIPS, 2024)

Predicting the Performance of Foundation Models via Agreement-on-the-Line. - Rahul Saxena; Taeyoun Kim; Aman Mehra; Christina Baek; J. Zico Kolter; Aditi Raghunathan (NeurIPS, 2024)

Rethinking LLM Memorization through the Lens of Adversarial Compression. - Avi Schwarzschild; Zhili Feng; Pratyush Maini; Zachary C. Lipton; J. Zico Kolter (NeurIPS, 2024)

Improving Alignment and Robustness with Circuit Breakers. - Andy Zou; Long Phan; Justin Wang; Derek Duenas; Maxwell Lin; Maksym Andriushchenko; J. Zico Kolter; Matt Fredrikson; Dan Hendrycks (NeurIPS, 2024)

Computing Low-Entropy Couplings for Large-Support Distributions. - Samuel Sokota; Dylan Sam; Christian Schröder de Witt; Spencer Compton; Jakob N. Foerster; J. Zico Kolter (UAI, 2024)

TOFU: A Task of Fictitious Unlearning for LLMs. - Pratyush Maini; Zhili Feng; Avi Schwarzschild; Zachary C. Lipton; J. Zico Kolter (CoRR, 2024)

An Axiomatic Approach to Model-Agnostic Concept Explanations. - Zhili Feng; Michal Moshkovitz; Dotan Di Castro; J. Zico Kolter (CoRR, 2024)

Bayesian Neural Networks with Domain Knowledge Priors. - Dylan Sam; Rattana Pukdee; Daniel P. Jeong; Yewon Byun; J. Zico Kolter (CoRR, 2024)

Massive Activations in Large Language Models. - Mingjie Sun; Xinlei Chen; J. Zico Kolter; Zhuang Liu 003 (CoRR, 2024)

AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs. - Victor Akinwande; J. Zico Kolter (CoRR, 2024)

Forcing Diffuse Distributions out of Language Models. - Yiming Zhang; Avi Schwarzschild; Nicholas Carlini; Zico Kolter; Daphne Ippolito (CoRR, 2024)

Improving Alignment and Robustness with Circuit Breakers. - Andy Zou; Long Phan; Justin Wang; Derek Duenas; Maxwell Lin; Maksym Andriushchenko; Rowan Wang; Zico Kolter; Matt Fredrikson; Dan Hendrycks (CoRR, 2024)

Consistency Models Made Easy. - Zhengyang Geng; Ashwini Pokle; William Luo; Justin Lin; J. Zico Kolter (CoRR, 2024)

FUSE-ing Language Models: Zero-Shot Adapter Discovery for Prompt Optimization Across Tokenizers. - Joshua Nathaniel Williams; J. Zico Kolter (CoRR, 2024)

Prompt Recovery for Image Generation Models: A Comparative Study of Discrete Optimizers. - Joshua Nathaniel Williams; Avi Schwarzschild; J. Zico Kolter (CoRR, 2024)

AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents. - Maksym Andriushchenko; Alexandra Souly; Mateusz Dziemian; Derek Duenas; Maxwell Lin; Justin Wang; Dan Hendrycks; Andy Zou; Zico Kolter; Matt Fredrikson; Eric Winsor; Jerome Wynne; et al. (CoRR, 2024)

Mimetic Initialization Helps State Space Models Learn to Recall. - Asher Trockman; Hrayr Harutyunyan; J. Zico Kolter; Sanjiv Kumar; Srinadh Bhojanapalli (CoRR, 2024)

Rethinking Distance Metrics for Counterfactual Explainability. - Joshua Nathaniel Williams; Anurag Katakkar; Hoda Heidari; J. Zico Kolter (CoRR, 2024)

Inference Optimal VLMs Need Only One Visual Token but Larger Models. - Kevin Y. Li; Sachin Goyal; João D. Semedo; J. Zico Kolter (CoRR, 2024)

Blind Inverse Problem Solving Made Easy by Text-to-Image Latent Diffusion. - Michail Dontas; Yutong He; Naoki Murata; Yuki Mitsufuji; J. Zico Kolter; Ruslan Salakhutdinov (CoRR, 2024)

HyperCLIP: Adapting Vision-Language models with Hypernetworks. - Victor Akinwande; Mohammad Sadegh Norouzzadeh; Devin Willmott; Anna Bair; Madan Ravi Ganesh; J. Zico Kolter (CoRR, 2024)

Text Descriptions are Compressive and Invariant Representations for Visual Learning. - Zhili Feng; Anna Bair; J. Zico Kolter (Trans. Mach. Learn. Res., 2024)

Theory of Agreement-on-the-Line in Linear Models and Gaussian Data. - Christina Baek; Aditi Raghunathan; J. Zico Kolter (AISTATS, 2025)

Understanding Optimization in Deep Learning with Central Flows. - Jeremy Cohen 001; Alex Damian; Ameet Talwalkar; J. Zico Kolter; Jason D. Lee (ICLR, 2025)

AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents. - Maksym Andriushchenko; Alexandra Souly; Mateusz Dziemian; Derek Duenas; Maxwell Lin; Justin Wang; Dan Hendrycks; Andy Zou; J. Zico Kolter; Matt Fredrikson; Yarin Gal; Xander Davies (ICLR, 2025)

Compute-Optimal LLMs Provably Generalize Better with Scale. - Marc Anton Finzi; Sanyam Kapoor; Diego Granziol; Anming Gu; Christopher De Sa; J. Zico Kolter; Andrew Gordon Wilson (ICLR, 2025)

Consistency Models Made Easy. - Zhengyang Geng; Ashwini Pokle; Weijian Luo; Justin Lin; J. Zico Kolter (ICLR, 2025)

Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance. - Sachin Goyal; Christina Baek; J. Zico Kolter; Aditi Raghunathan (ICLR, 2025)

Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws. - Yiding Jiang; Allan Zhou; Zhili Feng; Sadhika Malladi; J. Zico Kolter (ICLR, 2025)

Inference Optimal VLMs Need Fewer Visual Tokens and More Parameters. - Kevin Y. Li; Sachin Goyal; João D. Semedo; J. Zico Kolter (ICLR, 2025)

Neural Network Verification with Branch-and-Bound for General Nonlinearities. - Zhouxing Shi; Qirui Jin; Zico Kolter; Suman Jana; Cho-Jui Hsieh; Huan Zhang 001 (TACAS (1), 2025)

A Vision for Computational Decarbonization of Societal Infrastructure. - David E. Irwin 001; Prashant J. Shenoy; Mohammad Hajiesmaili; Walid A. Hanafy; Jimi Oke; Ramesh K. Sitaraman; Yuvraj Agarwal; Geoffrey J. Gordon; Zico Kolter; Deepak Rajagopal; Mani Srivastava 001; Vivienne Sze; et al. (IEEE Internet Comput., 2025)

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. - Yutong He; Alexander Robey; Naoki Murata; Yiding Jiang; Joshua Nathaniel Williams; George J. Pappas; Hamed Hassani; Yuki Mitsufuji; Ruslan Salakhutdinov; J. Zico Kolter (Trans. Mach. Learn. Res., 2025)

Finetuning CLIP to Reason about Pairwise Differences. - Dylan Sam; Devin Willmott; João D. Semedo; J. Zico Kolter (Trans. Mach. Learn. Res., 2025)

Predicting the Performance of Black-box LLMs through Self-Queries. - Dylan Sam; Marc Finzi; J. Zico Kolter (CoRR, 2025)

Reevaluating Policy Gradient Methods for Imperfect-Information Games. - Max Rudolph; Nathan Lichtle; Sobhan Mohammadpour; Alexandre M. Bayen; J. Zico Kolter; Amy Zhang 001; Gabriele Farina; Eugene Vinitsky; Samuel Sokota (CoRR, 2025)

Idiosyncrasies in Large Language Models. - Mingjie Sun; Yida Yin; Zhiqiu Xu; J. Zico Kolter; Zhuang Liu 003 (CoRR, 2025)

Training a Generally Curious Agent. - Fahim Tajwar; Yiding Jiang; Abitha Thankaraj; Sumaita Sadia Rahman; J. Zico Kolter; Jeff Schneider 001; Ruslan Salakhutdinov (CoRR, 2025)

Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners. - Daniele Paliotta; Junxiong Wang; Matteo Pagliardini; Kevin Y. Li; Aviv Bick; J. Zico Kolter; Albert Gu; François Fleuret; Tri Dao (CoRR, 2025)

Unnatural Languages Are Not Bugs but Features for LLMs. - Keyu Duan; Yiran Zhao 006; Zhili Feng; Jinjie Ni; Tianyu Pang; Qian Liu 012; Tianle Cai; Longxu Dou; Kenji Kawaguchi; Anirudh Goyal; J. Zico Kolter; Michael Qizhe Shieh (CoRR, 2025)

Weight Ensembling Improves Reasoning in Language Models. - Xingyu Dang; Christina Baek; Kaiyue Wen; Zico Kolter; Aditi Raghunathan (CoRR, 2025)

Looking beyond the next token. - Abitha Thankaraj; Yiding Jiang; J. Zico Kolter; Yonatan Bisk (CoRR, 2025)

Antidistillation Sampling. - Yash Savani; Asher Trockman; Zhili Feng; Avi Schwarzschild; Alexander Robey; Marc Finzi; J. Zico Kolter (CoRR, 2025)

Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning. - Yixuan Even Xu; Yash Savani; Fei Fang 001; Zico Kolter (CoRR, 2025)

Safety Pretraining: Toward the Next Generation of Safe AI. - Pratyush Maini; Sachin Goyal; Dylan Sam; Alexander Robey; Yash Savani; Yiding Jiang; Andy Zou; Zacharcy C. Lipton; J. Zico Kolter (CoRR, 2025)

Contextures: Representations from Contexts. - Runtian Zhai; Kai Yang; Che-Ping Tsai; Burak Varici; Zico Kolter; Pradeep Ravikumar (CoRR, 2025)

Mean Flows for One-step Generative Modeling. - Zhengyang Geng; Mingyang Deng; Xingjian Bai; J. Zico Kolter; Kaiming He (CoRR, 2025)

Existing Large Language Model Unlearning Evaluations Are Inconclusive. - Zhili Feng; Yixuan Even Xu; Alexander Robey; Robert Kirk; Xander Davies; Yarin Gal; Avi Schwarzschild; J. Zico Kolter (CoRR, 2025)

Adversarial Attacks on Robotic Vision Language Action Models. - Eliot Krzysztof Jones; Alexander Robey; Andy Zou; Zachary Ravichandran; George J. Pappas; Hamed Hassani; Matt Fredrikson; J. Zico Kolter (CoRR, 2025)

Accelerating Diffusion Models in Offline RL via Reward-Aware Consistency Trajectory Distillation. - Xintong Duan; Yutong He; Fahim Tajwar; Ruslan Salakhutdinov; J. Zico Kolter; Jeff G. Schneider (CoRR, 2025)

OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics. - Vineeth Dorna; Anmol Mekala; Wenlong Zhao 001; Andrew McCallum; Zachary C. Lipton; J. Zico Kolter; Pratyush Maini (CoRR, 2025)

OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents. - Thomas Kuntz; Agatha Duzan; Hao Zhao; Francesco Croce; Zico Kolter; Nicolas Flammarion; Maksym Andriushchenko (CoRR, 2025)

Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition. - Andy Zou; Maxwell Lin; Eliot Krzysztof Jones; Micha Nowak; Mateusz Dziemian; Nick Winter; Alexander Grattan; Valent Nathanael; Ayla Croft; Xander Davies; Jai Patel; Robert Kirk; et al. (CoRR, 2025)