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Amjad Almahairi
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2020 – today
- 2024
- [i19]Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M. Waleed Kadous, Ion Stoica:
RouteLLM: Learning to Route LLMs with Preference Data. CoRR abs/2406.18665 (2024) - 2023
- [c12]Suzanna Sia, Anton Belyy, Amjad Almahairi, Madian Khabsa, Luke Zettlemoyer, Lambert Mathias:
Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI. AAAI 2023: 9837-9845 - [c11]Anastasia Razdaibiedina, Yuning Mao, Madian Khabsa, Mike Lewis, Rui Hou, Jimmy Ba, Amjad Almahairi:
Residual Prompt Tuning: improving prompt tuning with residual reparameterization. ACL (Findings) 2023: 6740-6757 - [c10]Kuan-Hao Huang
, Liang Tan, Rui Hou, Sinong Wang, Amjad Almahairi, Ruty Rinott:
Learning Easily Updated General Purpose Text Representations with Adaptable Task-Specific Prefix. EMNLP (Findings) 2023: 7422-7430 - [c9]Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, Amjad Almahairi:
Progressive Prompts: Continual Learning for Language Models. ICLR 2023 - [i18]Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, Amjad Almahairi:
Progressive Prompts: Continual Learning for Language Models. CoRR abs/2301.12314 (2023) - [i17]Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, Jimmy Ba, Amjad Almahairi:
Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization. CoRR abs/2305.03937 (2023) - [i16]Kuan-Hao Huang, Liang Tan, Rui Hou, Sinong Wang, Amjad Almahairi, Ruty Rinott:
Learning Easily Updated General Purpose Text Representations with Adaptable Task-Specific Prefixes. CoRR abs/2305.13499 (2023) - [i15]Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, Thomas Scialom:
Llama 2: Open Foundation and Fine-Tuned Chat Models. CoRR abs/2307.09288 (2023) - [i14]Shraman Pramanick, Guangxing Han, Rui Hou, Sayan Nag, Ser-Nam Lim, Nicolas Ballas, Qifan Wang, Rama Chellappa, Amjad Almahairi:
Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model. CoRR abs/2312.12423 (2023) - 2022
- [c8]Yuning Mao, Lambert Mathias, Rui Hou, Amjad Almahairi, Hao Ma, Jiawei Han, Scott Yih, Madian Khabsa:
UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning. ACL (1) 2022: 6253-6264 - [i13]Suzanna Sia, Anton Belyy, Amjad Almahairi, Madian Khabsa, Luke Zettlemoyer, Lambert Mathias:
Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI. CoRR abs/2205.12469 (2022) - [i12]Siddharth Verma, Yuchen Lu, Rui Hou, Hanchao Yu, Nicolas Ballas, Madian Khabsa, Amjad Almahairi:
Uniform Masking Prevails in Vision-Language Pretraining. CoRR abs/2212.05195 (2022) - 2021
- [i11]Yuning Mao, Lambert Mathias, Rui Hou, Amjad Almahairi, Hao Ma, Jiawei Han, Wen-tau Yih, Madian Khabsa:
UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning. CoRR abs/2110.07577 (2021) - 2020
- [c7]Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien:
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR 2020 - [c6]Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville:
Unsupervised Learning of Dense Visual Representations. NeurIPS 2020 - [i10]Pedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville:
Unsupervised Learning of Dense Visual Representations. CoRR abs/2011.05499 (2020)
2010 – 2019
- 2019
- [c5]Mai Oudah, Amjad Almahairi, Nizar Habash:
The Impact of Preprocessing on Arabic-English Statistical and Neural Machine Translation. MTSummit (1) 2019: 214-221 - [i9]Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien:
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR abs/1906.04848 (2019) - [i8]Jacob Leygonie, Jennifer She, Amjad Almahairi, Sai Rajeswar, Aaron C. Courville:
Adversarial Computation of Optimal Transport Maps. CoRR abs/1906.09691 (2019) - [i7]Mai Oudah, Amjad Almahairi, Nizar Habash:
The Impact of Preprocessing on Arabic-English Statistical and Neural Machine Translation. CoRR abs/1906.11751 (2019) - 2018
- [c4]Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron C. Courville:
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data. ICML 2018: 195-204 - [i6]Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, Aaron C. Courville:
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data. CoRR abs/1802.10151 (2018) - [i5]Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville:
Learning Distributed Representations from Reviews for Collaborative Filtering. CoRR abs/1806.06875 (2018) - 2017
- [c3]Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville:
Calibrating Energy-based Generative Adversarial Networks. ICLR (Poster) 2017 - [i4]Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville:
Calibrating Energy-based Generative Adversarial Networks. CoRR abs/1702.01691 (2017) - 2016
- [c2]Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville:
Dynamic Capacity Networks. ICML 2016: 2549-2558 - [i3]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:
Theano: A Python framework for fast computation of mathematical expressions. CoRR abs/1605.02688 (2016) - [i2]Amjad Almahairi, Kyunghyun Cho, Nizar Habash, Aaron C. Courville:
First Result on Arabic Neural Machine Translation. CoRR abs/1606.02680 (2016) - 2015
- [c1]Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville:
Learning Distributed Representations from Reviews for Collaborative Filtering. RecSys 2015: 147-154 - [i1]Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville:
Dynamic Capacity Networks. CoRR abs/1511.07838 (2015)
Coauthor Index
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