Thickstun, John

11 publications

NeurIPS 2025 Linearly Constrained Diffusion Implicit Models Vivek Jayaram, Ira Kemelmacher-Shlizerman, Steve Seitz, John Thickstun

TMLR 2024 Anticipatory Music Transformer John Thickstun, David Leo Wright Hall, Chris Donahue, Percy Liang

TMLR 2024 Robust Distortion-Free Watermarks for Language Models Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang

TMLR 2023 Evaluating Human-Language Model Interaction Mina Lee, Megha Srivastava, Amelia Hardy, John Thickstun, Esin Durmus, Ashwin Paranjape, Ines Gerard-Ursin, Xiang Lisa Li, Faisal Ladhak, Frieda Rong, Rose E Wang, Minae Kwon, Joon Sung Park, Hancheng Cao, Tony Lee, Rishi Bommasani, Michael S. Bernstein, Percy Liang

JMLR 2023 MAUVE Scores for Generative Models: Theory and Practice Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaid Harchaoui

NeurIPS 2022 Diffusion-LM Improves Controllable Text Generation Xiang Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B Hashimoto

L4DC 2021 Faster Policy Learning with Continuous-Time Gradients Samuel Ainsworth, Kendall Lowrey, John Thickstun, Zaid Harchaoui, Siddhartha Srinivasa

NeurIPS 2021 MAUVE: Measuring the Gap Between Neural Text and Human Text Using Divergence Frontiers Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaid Harchaoui

ICML 2021 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics Vivek Jayaram, John Thickstun

ICML 2020 Source Separation with Deep Generative Priors Vivek Jayaram, John Thickstun

ICLR 2017 Learning Features of Music from Scratch John Thickstun, Zaïd Harchaoui, Sham M. Kakade