[C46] Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal Behbahani, Aleksandra Faust, “Training Language Models to Self-Correct via Reinforcement Learning,” International Conference of Learning Representations (ICLR), May 2025. (Oral -- 1.8% acceptance rate). Press: VentureBeat, Marktech Post.
[C45] Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust, ”Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models,” International Conference of Learning Representations (ICLR), May 2025.
[C44] Wilson Yan, Matei Zaharia, Volodymyr Mnih, Aleksandra Faust, Pieter Abbeel, Hao Liu, “ElasticTok: Adaptive Tokenization for Image and Video,” International Conference of Learning Representations (ICLR), May 2025.
[C43] Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle, “Many-Shot In-Context Learning,” The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS) 2024. (Spotlight).
[C42] Hiroki Furuta, Kuang-Huei Lee, Shixiang Shane Gu, Yutaka Matsuo, Aleksandra Faust, Heiga Zen, Izzeddin Gur, “Geometric-Averaged Preference Optimization for Soft Preference Labels,” The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS) 2024.
[C41] Meredith Ringel Morris, Jascha Sohl-dickstein, Noah Fiedel, Tris Warkentin, Allan Dafoe, Aleksandra Faust, Clement Farabet, Shane Legg, “Levels of AGI: Operationalizing Progress on the Path to AGI,” Positional paper, International Conference on Machine Learning (ICML) 2024. (Spotlight – 3.5% acceptance rate). Press: Press: Wikipedia, Bloomberg, The Economist, ZDNET, Forbes, MIT Technology Review, VentureBeat
[C40] Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taiga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Aleksandra Faust, Pablo Samuel Castro, Sergey Levine, Aviral Kumar, Rishabh Agarwal, “Stop Regressing: The Unreasonable Effectiveness of Classification in Deep Reinforcement Learning,” International Conference on Machine Learning (ICML) 2024. (Oral – 1.5% acceptance rate)
[C39] Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust, “A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis,” International Conference of Learning Representations (ICLR), May 2024. (Oral – 1.17% acceptance rate) Press: MarkTechPost, Synced, Toward AI.
[C38] Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Shane Gu, Izzeddin Gur, “Multimodal Web Navigation with Instruction-Finetuned Foundation Models,” International Conference of Learning Representations (ICLR), May 2024.
[C37] Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Sharan Narang, Aakanksha Chowdhery, Noah Fiedel, Aleksandra Faust, “Understanding HTML with Large Language Models,” Findings of Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023
[C36] Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Zeyu Yang, Brandyn White, Aleksandra Faust, Rowan Thomas McAllister, Dragomir Anguelov, Benjamin Sapp Hide, “WayMax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research,” Conference on Neural Information Processing Systems (NeurIPS) 2023. Press: TechCrunch, TechTimes
[C35] Yujin Tang, Wenhao Yu, Jie Tan, Heiga Zen, Aleksandra Faust, Tatsuya Harada, “SayTap: Language to Quadrupedal Locomotion,” Conference on Robot Learning (CoRL), 2023. Press: Blog, Gizmodo, InterestingEngineering
[C34] Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Ben Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Drago Anguelov, Sergey Levine, “Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023. Blog,
[C33] Yazied Hasan, Ariana Villegas Suarez, Evan C. Carter, Aleksandra Faust, Lydia Tapia “Enhancing Value Estimation Policies by Post-Hoc Symmetry Exploitation in Motion Planning Tasks,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023.
[C32] Anish Muthali, Haotian Shen, Sampada Deglurkar, Michael H. Lim, Rebecca Roelofs, Aleksandra Faust, Claire J. Tomlin, “Multi-Agent Reachability Calibration with Conformal Prediction,” IEEE Conference on Decision and Control (CDC), 2023.
[C31] Abdus Salam Azad, Izzeddin Gur, Jasper Emhoff, Nathaniel Alexis, Aleksandra Faust, Pieter Abbeel, Ion Stoica, “CLUTR: Curriculum Learning via Unsupervised Task Representation Learning,” International Conference on Machine Learning (ICML), 2023.
[C30] Srivatsan Krishnan, Amir Yazdanbaksh, Shvetank Prakash, Jason Jabbour, Ikechukwu Uchendu, Susobhan Ghosh, Behzad Boroujerdian, Daniel Richins, Devashree Tripathy, Aleksandra Faust, Vijay Janapa Reddi, "ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design," International Symposium on Computer Architecture (ISCA) 2023. Press: Blog,
[C29] Sampada Deglurkar, Michael H. Lim, Johnathan Tucker, Zachary N. Sunberg, Aleksandra Faust, Claire J. Tomlin, "Compositional Learning-based Planning for Vision POMDPs," Learning for Dynamics & Control Conference (L4DC) 2023
[C28] Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul Whatmough, Aleksandra Faust, Sabrina M. Neuman Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, “Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles,” IEEE/ACM International Symposium on Microarchitecture (MICRO) 2022, IEEE Micro Top Picks 2023 Honorable Mention.
[C27] Yingjie Miao, Xingyou Song, John D Co-Reyes, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust, "Differentiable Architecture Search for Reinforcement Learning," The International Conference on Automated Machine Learning (AutoML), 2022. (19% acceptance rate).
[C26] Sungryull Sohn, Hyunjae Woo, Jongwook Choi, lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee, "Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization," Oral @ Uncertainty in Artificial Intelligence (UAI) 2022. (5% acceptance rate)
[C25] Sabrina M. Neuman, Brian Plancher, Bart Duisterhof, Srivatsan Krishnan, Colby Banbury, Mark Mazumder, Shvetank Prakash, Jason Jabbour, Aleksandra Faust, Guido de Croon, Vijay Janapa Reddi, "Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots," IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) special session on Low Power Autonomous Systems 2022.
[C24] Srivatsan Krishnan , Zishen Wan, Kshitij Bhardwaj, Ninad Jadhav,. Aleksandra Faust, Vijay Janapa Reddi, "Roofline Model for UAVs: A Visual Performance Model for Guiding Compute System Design in Autonomous Drones," IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2022
[C23] Su Wang, Ceslee Montgomery, Jordi Orbay, Vighnesh Birodkar, Aleksandra Faust, Izzeddin Gur, Natasha Jaques, Austin Waters, Jason Baldridge, Peter Anderson, "Less is More: Generating Grounded Navigation Instructions from Landmarks," IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2022
[C22] Michael Lim, Andy Zeng, Brian Ichter, Maryam Bandari, Erwin Coumans, Claire Tomlin, Stefan Schaal, Aleksandra Faust, "Multi-Task Learning with Sequence-Conditioned Transporter Networks," International Conference on Robotics and Automation (ICRA), 2022.
[C21] Marco Carmona, Dejan Milutinovic, Aleksandra Faust, "Metrics-only Training Neural Network for Switching among an Array of Feedback Controllers for Bicycle Model Navigation," American Controls Conference (ACC), 2022.
[C20] Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust, “Environment Generation for Zero-Shot Compositional Reinforcement Learning,” Conference on Neural Information Processing Systems (NeurIPS) 2021.
[C19] Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust, Guido C. H. E. de Croon, Vijay Janapa Reddi, "Tiny Robot Learning (tinyRL) for Source Seeking on a Nano Quadcopter," IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021, pp. 7242-7248.
[C19] Felipe Felix Arias,, Brian Ichter, Aleksandra Faust, Nancy M. Amato, “Avoidance Critical Probabilistic Roadmaps for Motion Planning in Dynamic Environments," IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021, pp. 10264-10270.
[C18] John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc Le, Honglak Lee, Aleksandra Faust, “Evolving Reinforcement Learning Algorithms,” Oral @ International Conference of Learning Representations (ICLR) 2021 (<2% acceptance rate) Press: Google AI Year in Review, Analytics India Magazine
[C17] Rose E. Wang, J. Chase Kew, Dennis Lee, Brian Ichter, Tsang-Wei Edward, Lee, Tingnan Zhang, Jie Tan, Aleksandra Faust, “Model-based Reinforcement Learning for Multiagent Goal Alignment,“ Conference on Robot Learning (CoRL) 2020. Website, Video. (34% acceptance rate). Press: Google AI Year in Review
[C16] Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar Duenez-Guzman, “Safe Policy Learning for Continuous Control,” Conference on Robot Learning (CoRL) 2020. (34% acceptance rate). Press: Google AI Year in Review,
[C15] J. Chase Kew, Brian Ichter, Maryam Bandari, Tsang-Wei Edward Lee, Aleksandra Faust, “Neural Collision Clearance Estimator for Batched Motion Planning,” The Workshop on the Algorithmic Foundations of Robotics (WAFR) 2020. Video
[C14] Xinlei Pan, Tingnan Zhang, Brian Ichter, Aleksandra Faust, Jie Tan, Sehoon Ha, “Zero-shot Imitation Learning from Demonstrations for Legged Robot Visual Navigation,” International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 679-685. Website
[C13] Brian Ichter, Edward Schmerling, Tsang-Wei Edward Lee, Aleksandra Faust, “Learned Critical Probabilistic Roadmaps for Robotic Motion Planning,” EEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 9535-9541. Video
[C12] Arpit Garg, Hao-Tien Lewis Chiang, Satomi Sugaya, Aleksandra Faust, Lydia Tapia, “Comparison of Deep Reinforcement Learning Policies to Formal Methods for Moving Obstacle Avoidance,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019.
[C11] Izzedin Gur, Ulrich Rueckert, Aleksandra Faust, Dilek Hakkani-Tur, “Learning to Navigate the Web,” International Conference of Learning Representations (ICLR), May 2019. (in top 10% of accepted papers, 31% acceptance rate). Press: ZDNet, Tech Register, Medium
[C10] Hao-Tien Chiang, Aleksandra Faust, Lydia Tapia, “Fast Swept Volume Estimation with Deep Learning,” The 13th International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018.
[C9] Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan, Wenzhi Cui, Aleksandra Faust, Vijay Janapa Reddi, “MAVBench: Micro Aerial Vehicle Benchmarking,” 51st IEEE/ACM International Symposium on Microarchitecture (MICRO) pp. 894-907, 2018. (21% acceptance rate).
[C8] Aleksandra Faust, James B. Aimone, Conrad D. James, Lydia Tapia, “Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting,” 57th IEEE Conference on Decision and Control (CDC), pp. 5999-6006, 2018. Press: ZDNet, Medium
[C7] Aleksandra Faust, Oscar Ramirez, Marek Fiser, Ken Oslund, Anthony Francis, James Davidson, Lydia Tapia, “PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning,” IEEE International Conference on Robotics and Automation (ICRA), pp. 5113-5120, Brisbane, Australia, 2018. Best paper in Service robotics. Press: Google AI Blog, VentureBeat, Packtpub, Medium
[C6] Aleksandra Faust, Hao-Tien Chiang, Nathanael Rackley, Lydia Tapia, “Avoiding Moving Obstacles with Stochastic Hybrid Dynamics Using PEARL: PrEference Appraisal Reinforcement Learning,” IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016, pp. 484-490.
[C5] Aleksandra Faust, Nick Malone, Lydia Tapia, “Preference-balancing Motion Planning under Stochastic Disturbances,” IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, 2015, pp. 3555-3562.
[C4] Rafael Figueroa, Aleksandra Faust, Patricio Cruz, Lydia Tapia, Rafael Fierro, "Reinforcement Learning for Balancing a Flying Inverted Pendulum," The 11th World Congress on Intelligent Control and Automation (WCICA), Shenyang, China, 2014.
[C3] Aleksandra Faust, Ivana Palunko, Patricio Cruz, Rafael Fierro, Lydia Tapia, “Learning Swing-free Trajectories for UAVs with a Suspended Load,” IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 2013, pp. 4887–4894.
[C2] Ivana Palunko, Aleksandra Faust, Patricio Cruz, Lydia Tapia, Rafael Fierro, "A Reinforcement Learning Approach to Suspended Load Manipulation with Aerial Robots," IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013, pp 4881–4886.
[C1] Peter B. Merkle, Antonio Gonzales, Aleksandra Faust, Kurt W. Larson, Jack C. Bartberger, Karl E. Horak, Manuel M. Trujillo, Nathan Reynolds Schanfein, Keith M. Tolk, Nairong Nancy Wang, “Reflective Particle Tag for Arms Control and Safeguards Authentication,” Institute of Nuclear Materials Management Annual Conference, Tucson, AZ, July 2009.