John Thickstun

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Percy LiangAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Zaid HarchaouiUniversity of WashingtonVerified email at uw.edu
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Yejin ChoiUniversity of Washington / Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Rowan ZellersOpenAIVerified email at cs.washington.edu
Swabha SwayamdiptaUniversity of Southern CaliforniaVerified email at usc.edu
Tatsunori HashimotoAssistant Professor, StanfordVerified email at stanford.edu
Xiang Lisa LiStanford UniversityVerified email at stanford.edu
Krishna PillutlaIIT MadrasVerified email at iitm.ac.in
Ishaan GulrajaniOpenAIVerified email at openai.com
Dean FosterAmazon, NYCVerified email at amazon.com
Vivek JayaramUniversity of WashingtonVerified email at cs.washington.edu
Rohith KuditipudiStanford UniversityVerified email at stanford.edu
Bhargavi ParanjapeUniversity of WashingtonVerified email at cs.washington.edu
Luke ZettlemoyerUniversity of Washington; MetaVerified email at cs.washington.edu
Mina LeeUniversity of ChicagoVerified email at uchicago.edu
Chris DonahueAssistant Professor, CMU CSD; Research Scientist, Google DeepMind (part time)Verified email at cmu.edu
Sewoong OhPaul G. Allen School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
John HewittVisiting Researcher, Google DeepMind.Verified email at stanford.edu
Jennifer BrennanGoogle ResearchVerified email at google.com

John Thickstun

Assistant Professor, Cornell University

Verified email at cornell.edu - Homepage

Machine Learning Generative Models Music Technology Natural Language Processing


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Diffusion-LM Improves Controllable Text Generation XL Li, J Thickstun, I Gulrajani, P Liang, TB Hashimoto Advances in Neural Information Processing Systems (Neurips), 2022	667	2022
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers K Pillutla, S Swayamdipta, R Zellers, J Thickstun, S Welleck, Y Choi, ... Advances in Neural Information Processing Systems (Neurips), 2021	296	2021
Learning Features of Music from Scratch J Thickstun, Z Harchaoui, S Kakade International Conference on Learning Representations (ICLR), 2017	246	2017
An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction B Paranjape, M Joshi, J Thickstun, H Hajishirzi, L Zettlemoyer Empirical Methods in Natural Language Processing (EMNLP), 2020	113	2020
Robust Distortion-free Watermarks for Language Models R Kuditipudi, J Thickstun, T Hashimoto, P Liang Transactions on Machine Learning Research (TMLR), 2024	106	2024
Evaluating Human-Language Model Interaction M Lee, M Srivastava, A Hardy, J Thickstun, E Durmus, A Paranjape, ... Transactions on Machine Learning Research (TMLR), 2023	102	2023
Invariances and Data Augmentation for Supervised Music Transcription J Thickstun, Z Harchaoui, DP Foster, SM Kakade International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2018	76	2018
Source Separation with Deep Generative Priors V Jayaram, J Thickstun International Conference on Machine Learning (ICML), 2020	44	2020
Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics V Jayaram, J Thickstun International Conference on Machine Learning (ICML), 2021	30	2021
Melody Transcription via Generative Pre-Training C Donahue, J Thickstun, P Liang International Society for Music Information Retrieval (ISMIR), 2022	21	2022
Convolutional Composer Classification H Verma, J Thickstun International Society for Music Information Retrieval (ISMIR), 2019	21	2019
Anticipatory Music Transformer J Thickstun, D Hall, C Donahue, P Liang Transactions on Machine Learning Research (TMLR), 2024	20	2024
The Transformer Model in Equations J Thickstun University of Washington, Technical Report, 2020	20	2020
Backpack Language Models J Hewitt, J Thickstun, CD Manning, P Liang Association for Computational Linguistics (ACL), 2023	19	2023
MAUVE Scores for Generative Models: Theory and Practice K Pillutla, L Liu, J Thickstun, S Welleck, S Swayamdipta, R Zellers, S Oh, ... Journal of Machine Learning Research (JMLR), 2023	15	2023
Coupled Recurrent Models for Polyphonic Music Composition J Thickstun, Z Harchaoui, DP Foster, SM Kakade International Society for Music Information Retrieval (ISMIR), 2019	14	2019
Faster Policy Learning with Continuous-Time Gradients S Ainsworth, K Lowrey, J Thickstun, Z Harchaoui, S Srinivasa Learning for Dynamics & Control (L4DC), 2021	12	2021
Rethinking Evaluation Methodology for Audio-to-Score Alignment J Thickstun, J Brennan, H Verma arXiv preprint arXiv:2009.14374, 2020	8	2020
Kantorovich-Rubinstein Duality J Thickstun University of Washington, Technical Report, 2020	8	2020
Mercer’s Theorem J Thickstun University of Washington, Technical Report, 2019	7	2019

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