Colin Raffel
Colin Raffel
UNC Chapel Hill and Hugging Face
Verified email at - Homepage
Cited by
Cited by
Exploring the limits of transfer learning with a unified text-to-text transformer
C Raffel*, N Shazeer*, A Roberts*, K Lee*, S Narang, M Matena, Y Zhou, ...
Journal of Machine Learning Research 21 (140), 1-67, 2020
librosa: Audio and music signal analysis in python
B McFee, C Raffel, D Liang, DPW Ellis, M McVicar, E Battenberg, O Nieto
Proceedings of the 14th python in science conference 8, 2015
Mixmatch: A holistic approach to semi-supervised learning
D Berthelot, N Carlini, I Goodfellow, N Papernot, A Oliver, C Raffel
Advances in Neural Information Processing Systems, 5050-5060, 2019
Fixmatch: Simplifying semi-supervised learning with consistency and confidence
K Sohn*, D Berthelot*, CL Li, Z Zhang, N Carlini, ED Cubuk, A Kurakin, ...
arXiv preprint arXiv:2001.07685, 2020
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688, 2016
Realistic evaluation of deep semi-supervised learning algorithms
A Oliver*, A Odena*, C Raffel*, ED Cubuk, ...
Advances in Neural Information Processing Systems, 3235-3246, 2018
Thermometer Encoding: One Hot Way To Resist Adversarial Examples
J Buckman*, A Roy*, C Raffel, I Goodfellow (* denotes equal contribution)
Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring
D Berthelot, N Carlini, ED Cubuk, A Kurakin, K Sohn, H Zhang, C Raffel
arXiv preprint arXiv:1911.09785, 2019
mT5: A massively multilingual pre-trained text-to-text transformer
L Xue, N Constant, A Roberts, M Kale, R Al-Rfou, A Siddhant, A Barua, ...
arXiv preprint arXiv:2010.11934, 2020
mir_eval: A Transparent Implementation of Common MIR Metrics
C Raffel, B McFee, EJ Humphrey, J Salamon, O Nieto, D Liang, DPW Ellis
Proc. of the 15th International Society for Music Information Retrieval …, 2014
A hierarchical latent vector model for learning long-term structure in music
A Roberts, J Engel, C Raffel, C Hawthorne, D Eck
International conference on machine learning, 4364-4373, 2018
Feed-forward networks with attention can solve some long-term memory problems
C Raffel, DPW Ellis
arXiv preprint arXiv:1512.08756, 2015
Extracting training data from large language models
N Carlini, F Tramer, E Wallace, M Jagielski, A Herbert-Voss, K Lee, ...
30th USENIX Security Symposium (USENIX Security 21), 2633-2650, 2021
Lasagne: first release
S Dieleman, J Schlüter, C Raffel, E Olson, SK Sĝnderby, D Nouri, ...
Zenodo: Geneva, Switzerland 3, 2015
How Much Knowledge Can You Pack Into the Parameters of a Language Model?
A Roberts*, C Raffel*, N Shazeer (* denotes equal contribution)
arXiv preprint arXiv:2002.08910, 2020
Imperceptible, robust, and targeted adversarial examples for automatic speech recognition
Y Qin, N Carlini, G Cottrell, I Goodfellow, C Raffel
International conference on machine learning, 5231-5240, 2019
Online and linear-time attention by enforcing monotonic alignments
C Raffel, MT Luong, PJ Liu, RJ Weiss, D Eck
International Conference on Machine Learning, 2837-2846, 2017
Onsets and frames: Dual-objective piano transcription
C Hawthorne, E Elsen, J Song, A Roberts, I Simon, C Raffel, J Engel, ...
arXiv preprint arXiv:1710.11153, 2017
Learning-based methods for comparing sequences, with applications to audio-to-midi alignment and matching
C Raffel
Columbia University, 2016
Monotonic chunkwise attention
CC Chiu*, C Raffel* (* denotes equal contribution)
arXiv preprint arXiv:1712.05382, 2017
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