Beutel, Alex

18 publications

ICLR 2025 First-Person Fairness in Chatbots Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai

TMLR 2024 Break It, Imitate It, Fix It: Robustness by Generating Human-like Attacks Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel

ICLRW 2024 Break It, Imitate It, Fix It: Robustness by Generating Human-like Attacks Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel

ICML 2024 Controlled Decoding from Language Models Sidharth Mudgal, Jong Lee, Harish Ganapathy, Yaguang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, Ahmad Beirami

NeurIPSW 2024 Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning Alex Beutel, Kai Yuanqing Xiao, Johannes Heidecke, Lilian Weng

ICMLW 2024 Rule Based Rewards for Fine-Grained LLM Safety Tong Mu, Alec Helyar, Johannes Heidecke, Joshua Achiam, Andrea Vallone, Ian D Kivlichan, Molly Lin, Alex Beutel, John Schulman, Lilian Weng

NeurIPS 2024 Rule Based Rewards for Language Model Safety Tong Mu, Alec Helyar, Johannes Heidecke, Joshua Achiam, Andrea Vallone, Ian Kivlichan, Molly Lin, Alex Beutel, John Schulman, Lilian Weng

NeurIPSW 2023 Controlled Decoding from Language Models Sidharth Mudgal, Jong Lee, Harish Ganapathy, YaGuang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Jilin Chen, Alex Beutel, Ahmad Beirami

NeurIPS 2023 Effective Robustness Against Natural Distribution Shifts for Models with Different Training Data Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin

NeurIPSW 2022 Striving for Data-Model Efficiency: Identifying Data Externalities on Group Performance Esther Rolf, Ben Packer, Alex Beutel, Fernando Diaz

JMLR 2022 Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

NeurIPS 2022 Understanding and Improving Robustness of Vision Transformers Through Patch-Based Negative Augmentation Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang

NeurIPS 2021 Improving Calibration Through the Relationship with Adversarial Robustness Yao Qin, Xuezhi Wang, Alex Beutel, Ed Chi

NeurIPSW 2021 Understanding and Improving Robustness of VisionTransformers Through Patch-Based NegativeAugmentation Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang

NeurIPS 2020 Fairness Without Demographics Through Adversarially Reweighted Learning Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Wook Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed Chi

AISTATS 2018 Factorized Recurrent Neural Architectures for Longer Range Dependence Francois Belletti, Alex Beutel, Sagar Jain, Ed Huai-hsin Chi

ICLR 2017 Joint Training of Ratings and Reviews with Recurrent Recommender Networks Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola

AISTATS 2014 Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric P. Xing