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2020 – today
- 2024
[j4]Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang:
Robust Distortion-free Watermarks for Language Models. Trans. Mach. Learn. Res. 2024 (2024)- [j3]John Thickstun, David Leo Wright Hall, Chris Donahue, Percy Liang:
Anticipatory Music Transformer. Trans. Mach. Learn. Res. 2024 (2024) - [i18]Vivek Jayaram, Ira Kemelmacher-Shlizerman, Steven M. Seitz, John Thickstun:
Constrained Diffusion Implicit Models. CoRR abs/2411.00359 (2024) - 2023
- [j2]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. J. Mach. Learn. Res. 24: 356:1-356:92 (2023) - [j1]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:
Evaluating Human-Language Model Interaction. Trans. Mach. Learn. Res. 2023 (2023) - [c12]John Hewitt, John Thickstun, Christopher D. Manning, Percy Liang:
Backpack Language Models. ACL (1) 2023: 9103-9125 - [i17]John Hewitt, John Thickstun, Christopher D. Manning, Percy Liang:
Backpack Language Models. CoRR abs/2305.16765 (2023) - [i16]John Thickstun, David Hall, Chris Donahue, Percy Liang:
Anticipatory Music Transformer. CoRR abs/2306.08620 (2023) - [i15]Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang:
Robust Distortion-free Watermarks for Language Models. CoRR abs/2307.15593 (2023) - 2022
- [c11]Chris Donahue, John Thickstun, Percy Liang:
Melody transcription via generative pre-training. ISMIR 2022: 485-492 - [c10]Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto:
Diffusion-LM Improves Controllable Text Generation. NeurIPS 2022 - [i14]Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto:
Diffusion-LM Improves Controllable Text Generation. CoRR abs/2205.14217 (2022) - [i13]Chris Donahue, John Thickstun, Percy Liang:
Melody transcription via generative pre-training. CoRR abs/2212.01884 (2022) - [i12]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:
Evaluating Human-Language Model Interaction. CoRR abs/2212.09746 (2022) - [i11]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. CoRR abs/2212.14578 (2022) - 2021
- [b1]John Thickstun:
Leveraging Generative Models for Music and Signal Processing. University of Washington, USA, 2021 - [c9]Vivek Jayaram, John Thickstun:
Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics. ICML 2021: 4807-4818 - [c8]Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa:
Faster Policy Learning with Continuous-Time Gradients. L4DC 2021: 1054-1067 - [c7]Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui:
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. NeurIPS 2021: 4816-4828 - [i10]Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaïd Harchaoui:
MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation. CoRR abs/2102.01454 (2021) - [i9]Vivek Jayaram, John Thickstun:
Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics. CoRR abs/2105.08164 (2021) - 2020
- [c6]Bhargavi Paranjape, Mandar Joshi, John Thickstun, Hannaneh Hajishirzi, Luke Zettlemoyer:
An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction. EMNLP (1) 2020: 1938-1952 - [c5]Vivek Jayaram, John Thickstun:
Source Separation with Deep Generative Priors. ICML 2020: 4724-4735 - [i8]Vivek Jayaram, John Thickstun:
Source Separation with Deep Generative Priors. CoRR abs/2002.07942 (2020) - [i7]Bhargavi Paranjape, Mandar Joshi, John Thickstun, Hannaneh Hajishirzi, Luke Zettlemoyer:
An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction. CoRR abs/2005.00652 (2020) - [i6]John Thickstun, Jennifer Brennan, Harsh Verma:
Rethinking Evaluation Methodology for Audio-to-Score Alignment. CoRR abs/2009.14374 (2020) - [i5]Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa:
Faster Policy Learning with Continuous-Time Gradients. CoRR abs/2012.06684 (2020)
2010 – 2019
- 2019
- [c4]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Coupled Recurrent Models for Polyphonic Music Composition. ISMIR 2019: 311-318 - [c3]Harsh Verma, John Thickstun:
Convolutional Composer Classification. ISMIR 2019: 549-556 - [i4]Harsh Verma, John Thickstun:
Convolutional Composer Classification. CoRR abs/1911.11737 (2019) - 2018
- [c2]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Invariances and Data Augmentation for Supervised Music Transcription. ICASSP 2018: 2241-2245 - [i3]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Coupled Recurrent Models for Polyphonic Music Composition. CoRR abs/1811.08045 (2018) - 2017
- [c1]John Thickstun, Zaïd Harchaoui, Sham M. Kakade:
Learning Features of Music From Scratch. ICLR (Poster) 2017 - [i2]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Invariances and Data Augmentation for Supervised Music Transcription. CoRR abs/1711.04845 (2017) - 2016
- [i1]John Thickstun, Zaïd Harchaoui, Sham M. Kakade:
Learning Features of Music from Scratch. CoRR abs/1611.09827 (2016)
Coauthor Index
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last updated on 2024-12-11 21:43 CET by the dblp team
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