Colin Raffel
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
47
Venues
9
Active years
2014–2025
Best venue rank
A*
Where they publish
Papers
47 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution. | Fengyuan Liu, Nikhil Kandpal, Colin Raffel |
| 2025 | ICML | The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions. | Gl Sena Altintas, Devin Kwok, Colin Raffel, David Rolnick |
| 2025 | ICML | Position: The Most Expensive Part of an LLM *should* be its Training Data. | Nikhil Kandpal, Colin Raffel |
| 2025 | ICML | Fishers for Free? Approximating the Fisher Information Matrix by Recycling the Squared Gradient Accumulator. | Yu Xin Li, Felix Dangel, Derek Tam, Colin Raffel |
| 2024 | ACL | DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows. | Ajay Patel, Colin Raffel, Chris Callison-Burch |
| 2024 | ICML | Learning to Route Among Specialized Experts for Zero-Shot Generalization. | Mohammed Muqeeth, Haokun Liu, Yufan Liu, Colin Raffel |
| 2023 | ACL | 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 |
| 2023 | ACL | ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning. | Shachar Don-Yehiya, Elad Venezian, Colin Raffel, Noam Slonim, Leshem Choshen |
| 2023 | ACL | 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 |
| 2023 | ACL | Evaluating the Factual Consistency of Large Language Models Through News Summarization. | Derek Tam, Anisha Mascarenhas, Shiyue Zhang, Sarah Kwan, Mohit Bansal, Colin Raffel |
| 2023 | EMNLP | Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Model. | Haikang Deng, Colin Raffel |
| 2023 | EMNLP | Knowledge is a Region in Weight Space for Fine-tuned Language Models. | Almog Gueta, Elad Venezian, Colin Raffel, Noam Slonim, Yoav Katz, Leshem Choshen |
| 2023 | ICLR | Bidirectional Language Models Are Also Few-shot Learners. | Ajay Patel, Bryan Li, Mohammad Sadegh Rasooli, Noah Constant, Colin Raffel, Chris Callison-Burch |
| 2023 | ICML | Large Language Models Struggle to Learn Long-Tail Knowledge. | Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel |
| 2023 | ICML | 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 |
| 2022 | ACL | 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 Fvry, 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 |
| 2022 | ACL | Learning with Limited Text Data. | Diyi Yang, Ankur P. Parikh, Colin Raffel |
| 2022 | EMNLP | 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 |
| 2022 | ICLR | 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 Fvry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush |
| 2022 | ICML | Deduplicating Training Data Mitigates Privacy Risks in Language Models. | Nikhil Kandpal, Eric Wallace, Colin Raffel |
| 2022 | ICML | 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 |
| 2021 | EMNLP | Do Transformer Modifications Transfer Across Implementations and Applications? | Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Fvry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel |
| 2021 | EMNLP | Improving and Simplifying Pattern Exploiting Training. | Derek Tam, Rakesh R. Menon, Mohit Bansal, Shashank Srivastava, Colin Raffel |
| 2021 | ICLR | Robust and Generalizable Visual Representation Learning via Random Convolutions. | Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, Marc Niethammer |
| 2021 | KDD | 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 |
| 2021 | NAACL | 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 |
| 2020 | ASPLOS | Learning-based Memory Allocation for C++ Server Workloads. | Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel |
| 2020 | EMNLP | How Much Knowledge Can You Pack Into the Parameters of a Language Model? | Adam Roberts, Colin Raffel, Noam Shazeer |
| 2020 | ICLR | 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 |
| 2020 | ICLR | Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions. | Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton |
| 2019 | ACL | 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 |
| 2019 | ICLR | Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer. | David Berthelot, Colin Raffel, Aurko Roy, Ian J. Goodfellow |
| 2019 | ICLR | Towards GAN Benchmarks Which Require Generalization. | Ishaan Gulrajani, Colin Raffel, Luke Metz |
| 2019 | ICML | Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition. | Yao Qin, Nicholas Carlini, Garrison W. Cottrell, Ian J. Goodfellow, Colin Raffel |
| 2018 | ICASSP | Learning Hard Alignments with Variational Inference. | Dieterich Lawson, Chung-Cheng Chiu, George Tucker, Colin Raffel, Kevin Swersky, Navdeep Jaitly |
| 2018 | ICLR | Thermometer Encoding: One Hot Way To Resist Adversarial Examples. | Jacob Buckman, Aurko Roy, Colin Raffel, Ian J. Goodfellow |
| 2018 | ICLR | Monotonic Chunkwise Attention. | Chung-Cheng Chiu, Colin Raffel |
| 2018 | ICLR | Realistic Evaluation of Semi-Supervised Learning Algorithms. | Avital Oliver, Augustus Odena, Colin Raffel, Ekin D. Cubuk, Ian J. Goodfellow |
| 2018 | ICML | Is Generator Conditioning Causally Related to GAN Performance? | Augustus Odena, Jacob Buckman, Catherine Olsson, Tom B. Brown, Christopher Olah, Colin Raffel, Ian J. Goodfellow |
| 2018 | ICML | A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music. | Adam Roberts, Jesse H. Engel, Colin Raffel, Curtis Hawthorne, Douglas Eck |
| 2017 | ICLR | Explaining the Learning Dynamics of Direct Feedback Alignment. | Justin Gilmer, Colin Raffel, Samuel S. Schoenholz, Maithra Raghu, Jascha Sohl-Dickstein |
| 2017 | ICLR | Training a Subsampling Mechanism in Expectation. | Colin Raffel, Dieterich Lawson |
| 2017 | ICML | Online and Linear-Time Attention by Enforcing Monotonic Alignments. | Colin Raffel, Minh-Thang Luong, Peter J. Liu, Ron J. Weiss, Douglas Eck |
| 2016 | AAAI | 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 |
| 2016 | ICASSP | Optimizing DTW-based audio-to-MIDI alignment and matching. | Colin Raffel, Daniel P. W. Ellis |
| 2016 | ICASSP | Pruning subsequence search with attention-based embedding. | Colin Raffel, Daniel P. W. Ellis |
| 2014 | ICASSP | Estimating timing and channel distortion across related signals. | Colin Raffel, Daniel P. W. Ellis |