Liu, Peter J.

15 publications

TMLR 2024 Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models Avi Singh, John D Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T Parisi, Abhishek Kumar, Alexander A Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura A Culp, Lechao Xiao, Maxwell Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel

ICML 2024 Scaling Exponents Across Parameterizations and Optimizers Katie E Everett, Lechao Xiao, Mitchell Wortsman, Alexander A Alemi, Roman Novak, Peter J Liu, Izzeddin Gur, Jascha Sohl-Dickstein, Leslie Pack Kaelbling, Jaehoon Lee, Jeffrey Pennington

ICLR 2024 Small-Scale Proxies for Large-Scale Transformer Training Instabilities Mitchell Wortsman, Peter J Liu, Lechao Xiao, Katie E Everett, Alexander A Alemi, Ben Adlam, John D Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith

ICLR 2024 Statistical Rejection Sampling Improves Preference Optimization Tianqi Liu, Yao Zhao, Rishabh Joshi, Misha Khalman, Mohammad Saleh, Peter J Liu, Jialu Liu

ICLR 2023 Calibrating Sequence Likelihood Improves Conditional Language Generation Yao Zhao, Mikhail Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh, Peter J Liu

ICLR 2023 Out-of-Distribution Detection and Selective Generation for Conditional Language Models Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J Liu

ICLR 2023 SMART: Sentences as Basic Units for Text Evaluation Reinald Kim Amplayo, Peter J Liu, Yao Zhao, Shashi Narayan

NeurIPSW 2023 Self-Evaluation Improves Selective Generation in Large Language Models Jie Ren, Yao Zhao, Tu Vu, Peter J Liu, Balaji Lakshminarayanan

NeurIPSW 2022 Improving the Robustness of Conditional Language Models by Detecting and Removing Input Noise Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J Liu

NeurIPSW 2022 Out-of-Distribution Detection and Selective Generation for Conditional Language Models Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J Liu

JMLR 2020 Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu

NeurIPS 2019 Likelihood Ratios for Out-of-Distribution Detection Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark Depristo, Joshua Dillon, Balaji Lakshminarayanan

ICLR 2018 Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs W. James Murdoch, Peter J. Liu, Bin Yu

ICLR 2018 Generating Wikipedia by Summarizing Long Sequences Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, Noam Shazeer

ICML 2017 Online and Linear-Time Attention by Enforcing Monotonic Alignments Colin Raffel, Minh-Thang Luong, Peter J. Liu, Ron J. Weiss, Douglas Eck