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We propose Conditional Adapter (CoDA), a parameter-efficient transfer learning method that also improves inference efficiency.
The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini · 2005
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The second pascal recognising textual entailment challenge
R Bar Haim, Ido Dagan, Bill Dolan, Lisa Ferro, Danilo Giampiccolo, Bernardo Magnini, and Idan Szpektor · 2006
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z Li, Madian Khabsa, Han Fang, and Hao Ma · 2006
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The third pascal recognizing textual entailment challenge
Danilo Giampiccolo, Bernardo Magnini, Ido Dagan, and William B Dolan · 2007
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The fifth pascal recognizing textual entailment challenge
Luisa Bentivogli, Peter Clark, Ido Dagan, and Danilo Giampiccolo · 2009
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Sequence transduction with recurrent neural networks
Alex Graves · 2012
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
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Nonlinear programming
Harold W Kuhn and Albert W Tucker · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Librispeech: an asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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Coordinate descent algorithms
Stephen J Wright · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
Song Han, Huizi Mao, and William J Dally · 2016
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Sequence-level knowledge distillation
Yoon Kim and Alexander M. Rush · 2016
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From softmax to sparsemax: A sparse model of attention and multi-label classification
Andre Martins and Ramon Astudillo · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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Outrageously large neural networks: The sparsely-gated mixture-of-experts layer
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Jax: composable transformations of python+ numpy programs
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, et al · 2018
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Shashi Narayan, Shay B. Cohen, and Mirella Lapata · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman · 2018
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To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu and Suyog Gupta · 2018
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BoolQ: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
Cited alongside, same era.
Ocr-vqa: Visual question answering by reading text in images
Anand Mishra, Shashank Shekhar, Ajeet Kumar Singh, and Anirban Chakraborty · 2019
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Improving transformer models by reordering their sublayers
Ofir Press, Noah A Smith, and Omer Levy · 2019
Cited alongside, same era.
Stabilized sparse scaling algorithms for entropy regularized transport problems
Bernhard Schmitzer · 2019
Cited alongside, same era.
Fast transformer decoding: One write-head is all you need
Noam Shazeer · 2019
Cited alongside, same era.
Docvqa: A dataset for vqa on document images
Minesh Mathew, Dimosthenis Karatzas, and CV Jawahar · 2021
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Dynamicvit: Efficient vision transformers with dynamic token sparsification
Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, and Cho-Jui Hsieh · 2021
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Hash layers for large sparse models
Stephen Roller, Sainbayar Sukhbaatar, Jason Weston, et al · 2021
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Searching for efficient transformers for language modeling
David So, Wojciech Mańke, Hanxiao Liu, Zihang Dai, Noam Shazeer, and Quoc V Le · 2021
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Vision transformer architecture search
Xiu Su, Shan You, Jiyang Xie, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, and Chang Xu · 2021
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Screen2words: Automatic mobile ui summarization with multimodal learning
Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, and Yang Li · 2021
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Lingvo: a modular and scalable framework for sequence-to-sequence modeling, 2019
Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, et al · 2019
Cited alongside, same era.
Well-read students learn better: On the importance of pre-training compact models
Iulia Turc, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Controlling computation versus quality for neural sequence models
Ankur Bapna, Naveen Arivazhagan, and Orhan Firat · 2020
Cited alongside, same era.
Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan · 2020
Cited alongside, same era.
Conformer: Convolution-augmented transformer for speech recognition
Anmol Gulati, James Qin, Chung-Cheng Chiu, Niki Parmar, Yu Zhang, Jiahui Yu, Wei Han, Shibo Wang, Zhengdong Zhang, Yonghui Wu, et al · 2020
Cited alongside, same era.
Flax: A neural network library and ecosystem for jax
Jonathan Heek, Anselm Levskaya, Avital Oliver, Marvin Ritter, Bertrand Rondepierre, Andreas Steiner, and Marc van Zee · 2020
Cited alongside, same era.
Libri-light: A benchmark for asr with limited or no supervision
J. Kahn, M. Rivière, W. Zheng, E. Kharitonov, Q. Xu, P. E. Mazaré, J. Karadayi, V. Liptchinsky, R. Collobert, C. Fuegen, T. Likhomanenko, G. Synnaeve, A. Joulin, A. Mohamed, and E. Dupoux · 2020
Cited alongside, same era.
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Exploring the landscape of distributional robustness for question answering models
Anas Awadalla, Mitchell Wortsman, Gabriel Ilharco, Sewon Min, Ian Magnusson, Hannaneh Hajishirzi, and Ludwig Schmidt · 2022
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Self-supervised learning with random-projection quantizer for speech recognition
Chung-Cheng Chiu, James Qin, Yu Zhang, Jiahui Yu, and Yonghui Wu · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
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Glam: Efficient scaling of language models with mixture-of-experts
Nan Du, Yanping Huang, Andrew M Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, et al · 2022
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LongT5: Efficient text-to-text transformer for long sequences
Mandy Guo, Joshua Ainslie, David Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, and Yinfei Yang · 2022
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Transformer quality in linear time
Weizhe Hua, Zihang Dai, Hanxiao Liu, and Quoc Le · 2022
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Pix2struct: Screenshot parsing as pretraining for visual language understanding
Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, and Kristina Toutanova · 2022
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Efficient transformers with dynamic token pooling, 2022
Piotr Nawrot, Jan Chorowski, Adrian Łańcucki, and Edoardo M. Ponti · 2022
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Scaling up models and data with t5x
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, and Andrea Gesmundo · 2022
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Confident adaptive language modeling
Tal Schuster, Adam Fisch, Jai Gupta, Mostafa Dehghani, Dara Bahri, Vinh Tran, Yi Tay, and Donald Metzler · 2022
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Spartan: Differentiable Sparsity via Regularized Transportation
Kai Sheng Tai, Taipeng Tian, and Ser-Nam Lim · 2022
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Overcoming catastrophic forgetting in zero-shot cross-lingual generation
Tu Vu, Aditya Barua, Brian Lester, Daniel Cer, Mohit Iyyer, and Noah Constant · 2022
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Structured pruning learns compact and accurate models
Mengzhou Xia, Zexuan Zhong, and Danqi Chen · 2022
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A-ViT: Adaptive tokens for efficient vision transformer
Hongxu Yin, Arash Vahdat, Jose M. Alvarez, Arun Mallya, Jan Kautz, and Pavlo Molchanov · 2022
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Bigssl: Exploring the frontier of large-scale semi-supervised learning for automatic speech recognition
Yu Zhang, Daniel S Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, et al · 2022
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Mixture-of-experts with expert choice routing, 2022
Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew Dai, Zhifeng Chen, Quoc Le, and James Laudon · 2022
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Colt5: Faster long-range transformers with conditional computation
Joshua Ainslie, Tao Lei, Michiel de Jong, Santiago Ontañón, Siddhartha Brahma, Yury Zemlyanskiy, David Uthus, Mandy Guo, James Lee-Thorp, Yi Tay, et al · 2023
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Token merging: Your ViT but faster
Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, and Judy Hoffman · 2023
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2023
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