Colin Raffel

According to our database, Colin Raffel authored at least 107 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Combining Machine Learning and Lifetime-Based Resource Management for Memory Allocation and Beyond.

Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel

Commun. ACM, April, 2024

Merging by Matching Models in Task Parameter Subspaces.

Derek Tam, Mohit Bansal, Colin Raffel

Trans. Mach. Learn. Res., 2024

Soft Merging of Experts with Adaptive Routing.

Mohammed Muqeeth, Haokun Liu, Colin Raffel

Trans. Mach. Learn. Res., 2024

A Survey on Data Selection for Language Models.

Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang

Trans. Mach. Learn. Res., 2024

Realistic Evaluation of Model Merging for Compositional Generalization.

Derek Tam, Yash Kant, Brian Lester, Igor Gilitschenski, Colin Raffel

CoRR, 2024

A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning.

Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni

CoRR, 2024

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

Guilherme Penedo, Hynek Kydlícek, Loubna Ben Allal, Anton Lozhkov, Margaret Mitchell, Colin Raffel, Leandro von Werra, Thomas Wolf

CoRR, 2024

Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models.

Bowen Pan, Yikang Shen, Haokun Liu, Mayank Mishra, Gaoyuan Zhang, Aude Oliva, Colin Raffel, Rameswar Panda

CoRR, 2024

Learning to Route Among Specialized Experts for Zero-Shot Generalization.

Mohammed Muqeeth, Haokun Liu, Yufan Liu, Colin Raffel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows.

Ajay Patel, Colin Raffel, Chris Callison-Burch

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Building Machine Learning Models Like Open Source Software.

Colin Raffel

Commun. ACM, February, 2023

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu

Trans. Mach. Learn. Res., 2023

Efficient Methods for Natural Language Processing: A Survey.

Marcos V. Treviso, Ji-Ung Lee, Tianchu Ji, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Colin Raffel, Pedro Henrique Martins, André F. T. Martins, Jessica Zosa Forde, Peter A. Milder, Edwin Simpson, Noam Slonim, Jesse Dodge, Emma Strubell, Niranjan Balasubramanian, Leon Derczynski, Iryna Gurevych, Roy Schwartz

Trans. Assoc. Comput. Linguistics, 2023

An Empirical Survey of Data Augmentation for Limited Data Learning in NLP.

Jiaao Chen, Derek Tam, Colin Raffel, Mohit Bansal, Diyi Yang

Trans. Assoc. Comput. Linguistics, 2023

Scaling Up Models and Data with t5x and seqio.

Adam Roberts, Hyung Won Chung, Gaurav Mishra, Anselm Levskaya, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Kehang Han, Michelle Casbon, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, Andrea Gesmundo

J. Mach. Learn. Res., 2023

Merging by Matching Models in Task Subspaces.

Derek Tam, Mohit Bansal, Colin Raffel

CoRR, 2023

Efficient Online Data Mixing For Language Model Pre-Training.

Alon Albalak, Liangming Pan, Colin Raffel, William Yang Wang

CoRR, 2023

ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization.

Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal

CoRR, 2023

NPEFF: Non-Negative Per-Example Fisher Factorization.

Michael Matena, Colin Raffel

CoRR, 2023

Resolving Interference When Merging Models.

Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, Mohit Bansal

CoRR, 2023

TIES-Merging: Resolving Interference When Merging Models.

Prateek Yadav, Derek Tam, Leshem Choshen, Colin A. Raffel, Mohit Bansal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scaling Data-Constrained Language Models.

Niklas Muennighoff, Alexander M. Rush, Boaz Barak, Teven Le Scao, Nouamane Tazi, Aleksandra Piktus, Sampo Pyysalo, Thomas Wolf, Colin A. Raffel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distributed Inference and Fine-tuning of Large Language Models Over The Internet.

Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A. Raffel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data.

Alon Albalak, Colin A. Raffel, William Yang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models.

Nikhil Kandpal, Brian Lester, Mohammed Muqeeth, Anisha Mascarenhas, Monty Evans, Vishal Baskaran, Tenghao Huang, Haokun Liu, Colin Raffel

Proceedings of the International Conference on Machine Learning, 2023

Large Language Models Struggle to Learn Long-Tail Knowledge.

Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel

Proceedings of the International Conference on Machine Learning, 2023

Bidirectional Language Models Are Also Few-shot Learners.

Ajay Patel, Bryan Li, Mohammad Sadegh Rasooli, Noah Constant, Colin Raffel, Chris Callison-Burch

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Knowledge is a Region in Weight Space for Fine-tuned Language Models.

Almog Gueta, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Model.

Haikang Deng, Colin Raffel

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Evaluating the Factual Consistency of Large Language Models Through News Summarization.

Derek Tam, Anisha Mascarenhas, Shiyue Zhang, Sarah Kwan, Mohit Bansal, Colin Raffel

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Crosslingual Generalization through Multitask Finetuning.

Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M. Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, Colin Raffel

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning.

Shachar Don-Yehiya, Elad Venezian, Colin Raffel, Noam Slonim, Leshem Choshen

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Petals: Collaborative Inference and Fine-tuning of Large Models.

Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Maksim Riabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2023

2022

Emergent Abilities of Large Language Models.

Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus

Trans. Mach. Learn. Res., 2022

ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models.

Linting Xue, Aditya Barua, Noah Constant, Rami Al-Rfou, Sharan Narang, Mihir Kale, Adam Roberts, Colin Raffel

Trans. Assoc. Comput. Linguistics, 2022

ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning.

Shachar Don-Yehiya, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen

CoRR, 2022

Evaluating the Factual Consistency of Large Language Models Through Summarization.

Derek Tam, Anisha Mascarenhas, Shiyue Zhang, Sarah Kwan, Mohit Bansal, Colin Raffel

CoRR, 2022

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilic, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, Jonathan Tow, Alexander M. Rush, Stella Biderman, Albert Webson, Pawan Sasanka Ammanamanchi, Thomas Wang, Benoît Sagot, Niklas Muennighoff, Albert Villanova del Moral, Olatunji Ruwase, Rachel Bawden, Stas Bekman, Angelina McMillan-Major, Iz Beltagy, Huu Nguyen, Lucile Saulnier, Samson Tan, Pedro Ortiz Suarez, Victor Sanh, Hugo Laurençon, Yacine Jernite, Julien Launay, Margaret Mitchell, Colin Raffel, Aaron Gokaslan, Adi Simhi, Aitor Soroa, Alham Fikri Aji, Amit Alfassy, Anna Rogers, Ariel Kreisberg Nitzav, Canwen Xu, Chenghao Mou, Chris Emezue, Christopher Klamm, Colin Leong, Daniel van Strien, David Ifeoluwa Adelani, et al.

CoRR, 2022

What Language Model to Train if You Have One Million GPU Hours?

Teven Le Scao, Thomas Wang, Daniel Hesslow, Lucile Saulnier, Stas Bekman, M. Saiful Bari, Stella Biderman, Hady Elsahar, Niklas Muennighoff, Jason Phang, Ofir Press, Colin Raffel, Victor Sanh, Sheng Shen, Lintang Sutawika, Jaesung Tae, Zheng Xin Yong, Julien Launay, Iz Beltagy

CoRR, 2022

Petals: Collaborative Inference and Fine-tuning of Large Models.

Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel

CoRR, 2022

Efficient Methods for Natural Language Processing: A Survey.

Marcos V. Treviso, Tianchu Ji, Ji-Ung Lee, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Pedro Henrique Martins, André F. T. Martins, Peter A. Milder, Colin Raffel, Edwin Simpson, Noam Slonim, Niranjan Balasubramanian, Leon Derczynski, Roy Schwartz

CoRR, 2022

What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?

Thomas Wang, Adam Roberts, Daniel Hesslow, Teven Le Scao, Hyung Won Chung, Iz Beltagy, Julien Launay, Colin Raffel

CoRR, 2022

Scaling Up Models and Data with t5x and seqio.

Adam Roberts, Hyung Won Chung, Anselm Levskaya, Gaurav Mishra, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, Andrea Gesmundo

CoRR, 2022

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts.

Stephen H. Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M. Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged Saeed AlShaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Mike Tian-Jian Jiang, Alexander M. Rush

CoRR, 2022

Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language.

Zhenlin Xu, Marc Niethammer, Colin Raffel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Combinatorial Perspective on the Optimization of Shallow ReLU Networks.

Michael Matena, Colin Raffel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Merging Models with Fisher-Weighted Averaging.

Michael Matena, Colin Raffel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning.

Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, Colin Raffel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization?

Thomas Wang, Adam Roberts, Daniel Hesslow, Teven Le Scao, Hyung Won Chung, Iz Beltagy, Julien Launay, Colin Raffel

Proceedings of the International Conference on Machine Learning, 2022

Deduplicating Training Data Mitigates Privacy Risks in Language Models.

Nikhil Kandpal, Eric Wallace, Colin Raffel

Proceedings of the International Conference on Machine Learning, 2022

Multitask Prompted Training Enables Zero-Shot Task Generalization.

Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush

Proceedings of the Tenth International Conference on Learning Representations, 2022

What Language Model to Train if You Have One Million GPU Hours?

Teven Le Scao, Thomas Wang, Daniel Hesslow, Stas Bekman, M. Saiful Bari, Stella Biderman, Hady Elsahar, Niklas Muennighoff, Jason Phang, Ofir Press, Colin Raffel, Victor Sanh, Sheng Shen, Lintang Sutawika, Jaesung Tae, Zheng Xin Yong, Julien Launay, Iz Beltagy

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Learning with Limited Text Data.

Diyi Yang, Ankur P. Parikh, Colin Raffel

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts.

Stephen H. Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M. Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged Saeed AlShaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Dragomir R. Radev, Mike Tian-Jian Jiang, Alexander M. Rush

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022

2021

Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP.

Sabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, Colin Raffel, Manan Dey, Matthias Gallé, Arun Raja, Chenglei Si, Wilson Y. Lee, Benoît Sagot, Samson Tan

CoRR, 2021

Multitask Prompted Training Enables Zero-Shot Task Generalization.

Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, Alexander M. Rush

CoRR, 2021

Extracting Training Data from Large Language Models.

Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel

Proceedings of the 30th USENIX Security Symposium, 2021

Training Neural Networks with Fixed Sparse Masks.

Yi-Lin Sung, Varun Nair, Colin Raffel

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer.

Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, Colin Raffel

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition.

Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chi-wen Kan

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Robust and Generalizable Visual Representation Learning via Random Convolutions.

Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, Marc Niethammer

Proceedings of the 9th International Conference on Learning Representations, 2021

Improving and Simplifying Pattern Exploiting Training.

Derek Tam, Rakesh R. Menon, Mohit Bansal, Shashank Srivastava, Colin Raffel

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Do Transformer Modifications Transfer Across Implementations and Applications?

Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

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

J. Mach. Learn. Res., 2020

WT5?! Training Text-to-Text Models to Explain their Predictions.

Sharan Narang, Colin Raffel, Katherine Lee, Adam Roberts, Noah Fiedel, Karishma Malkan

CoRR, 2020

Deflecting Adversarial Attacks.

Yao Qin, Nicholas Frosst, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton

CoRR, 2020

Top-K Training of GANs: Improving Generators by Making Critics Less Critical.

Samarth Sinha, Anirudh Goyal, Colin Raffel, Augustus Odena

CoRR, 2020

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence.

Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples.

Samarth Sinha, Zhengli Zhao, Anirudh Goyal, Colin Raffel, Augustus Odena

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned.

Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions.

Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton

Proceedings of the 8th International Conference on Learning Representations, 2020

ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring.

David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel

Proceedings of the 8th International Conference on Learning Representations, 2020

How Much Knowledge Can You Pack Into the Parameters of a Language Model?

Adam Roberts, Colin Raffel, Noam Shazeer

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning-based Memory Allocation for C++ Server Workloads.

Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel

Proceedings of the ASPLOS '20: Architectural Support for Programming Languages and Operating Systems, 2020

2019

ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring.

David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel

CoRR, 2019

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling.

Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia Xu Chen, Ye Jia, Anjuli Kannan, Tara N. Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George F. Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel Bacchiani, Thomas B. Jablin, Robert Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon

CoRR, 2019

MixMatch: A Holistic Approach to Semi-Supervised Learning.

David Berthelot, Nicholas Carlini, Ian J. Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition.

Yao Qin, Nicholas Carlini, Garrison W. Cottrell, Ian J. Goodfellow, Colin Raffel

Proceedings of the 36th International Conference on Machine Learning, 2019

Towards GAN Benchmarks Which Require Generalization.

Ishaan Gulrajani, Colin Raffel, Luke Metz

Proceedings of the 7th International Conference on Learning Representations, 2019

Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer.

David Berthelot, Colin Raffel, Aurko Roy, Ian J. Goodfellow

Proceedings of the 7th International Conference on Learning Representations, 2019

Monotonic Infinite Lookback Attention for Simultaneous Machine Translation.

Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, Chung-Cheng Chiu, Semih Yavuz, Ruoming Pang, Wei Li, Colin Raffel

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Hickle: A HDF5-based python pickle replacement.

Danny C. Price, Sebastien Celles, Pieter T. Eendebak, Michael M. McKerns, Eben M. Olson, Colin Raffel, Bairen Yi

J. Open Source Softw., 2018

Learning a Latent Space of Multitrack Measures.

Ian Simon, Adam Roberts, Colin Raffel, Jesse H. Engel, Curtis Hawthorne, Douglas Eck

CoRR, 2018

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms.

Avital Oliver, Augustus Odena, Colin Raffel, Ekin Dogus Cubuk, Ian J. Goodfellow

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Onsets and Frames: Dual-Objective Piano Transcription.

Curtis Hawthorne, Erich Elsen, Jialin Song, Adam Roberts, Ian Simon, Colin Raffel, Jesse H. Engel, Sageev Oore, Douglas Eck

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music.

Adam Roberts, Jesse H. Engel, Colin Raffel, Curtis Hawthorne, Douglas Eck

Proceedings of the 35th International Conference on Machine Learning, 2018

Is Generator Conditioning Causally Related to GAN Performance?

Augustus Odena, Jacob Buckman, Catherine Olsson, Tom B. Brown, Christopher Olah, Colin Raffel, Ian J. Goodfellow

Proceedings of the 35th International Conference on Machine Learning, 2018

Realistic Evaluation of Semi-Supervised Learning Algorithms.

Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow

Proceedings of the 6th International Conference on Learning Representations, 2018

Monotonic Chunkwise Attention.

Chung-Cheng Chiu, Colin Raffel

Proceedings of the 6th International Conference on Learning Representations, 2018

Thermometer Encoding: One Hot Way To Resist Adversarial Examples.

Jacob Buckman, Aurko Roy, Colin Raffel, Ian J. Goodfellow

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Hard Alignments with Variational Inference.

Dieterich Lawson, Chung-Cheng Chiu, George Tucker, Colin Raffel, Kevin Swersky, Navdeep Jaitly

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Online and Linear-Time Attention by Enforcing Monotonic Alignments.

Colin Raffel, Minh-Thang Luong, Peter J. Liu, Ron J. Weiss, Douglas Eck

Proceedings of the 34th International Conference on Machine Learning, 2017

Training a Subsampling Mechanism in Expectation.

Colin Raffel, Dieterich Lawson

Proceedings of the 5th International Conference on Learning Representations, 2017

Explaining the Learning Dynamics of Direct Feedback Alignment.

Justin Gilmer, Colin Raffel, Samuel S. Schoenholz, Maithra Raghu, Jascha Sohl-Dickstein

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching.

Colin Raffel

PhD thesis, 2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

Extracting Ground-Truth Information from MIDI Files: A MIDIfesto.

Colin Raffel, Daniel P. W. Ellis

Proceedings of the 17th International Society for Music Information Retrieval Conference, 2016

Pruning subsequence search with attention-based embedding.

Colin Raffel, Daniel P. W. Ellis

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Optimizing DTW-based audio-to-MIDI alignment and matching.

Colin Raffel, Daniel P. W. Ellis

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games Using Convolutional Networks.

Nikolai Yakovenko, Liangliang Cao, Colin Raffel, James Fan

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games.

Nikolai Yakovenko, Liangliang Cao, Colin Raffel, James Fan

CoRR, 2015

Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems.

Colin Raffel, Daniel P. W. Ellis

CoRR, 2015

librosa: Audio and Music Signal Analysis in Python.

Brian McFee, Colin Raffel, Dawen Liang, Daniel P. W. Ellis, Matt McVicar, Eric Battenberg, Oriol Nieto

Proceedings of the 14th Python in Science Conference 2015 (SciPy 2015), Austin, Texas, July 6, 2015

Large-Scale Content-Based Matching of MIDI and Audio Files.

Colin Raffel, Daniel P. W. Ellis

Proceedings of the 16th International Society for Music Information Retrieval Conference, 2015

2014

MIR_EVAL: A Transparent Implementation of Common MIR Metrics.

Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, Daniel P. W. Ellis

Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

Estimating timing and channel distortion across related signals.

Colin Raffel, Daniel P. W. Ellis

Proceedings of the IEEE International Conference on Acoustics, 2014

2010

The Lattice Harp: A New Hybrid Instrument And Controller.

Colin Raffel, Nick Kruge, Diane Douglas, Edgar Berdahl, Wendy Ju

Proceedings of the 2010 International Computer Music Conference, 2010