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Real-world applications of neural language models often involve running many different models over the same corpus.
Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov. 2019 · 1901
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Assessing bert’s syntactic abilities
Yoav Goldberg. 2019 · 1901
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019b · 1907
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Does bert make any sense? interpretable word sense disambiguation with contextualized embeddings
Gregor Wiedemann, Steffen Remus, Avi Chawla, and Chris Biemann. 2019 · 1909
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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, and Peter J Liu. 2019 · 1910
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
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What would elsa do? freezing layers during transformer fine-tuning
Jaejun Lee, Raphael Tang, and Jimmy J. Lin. 2019 · 1911
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Introduction to the bio-entity recognition task at jnlpba
Nigel Collier and Jin-Dong Kim. 2004 · 2004
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On the effect of dropping layers of pre-trained transformer models
Hassan Sajjad, Fahim Dalvi, Nadir Durrani, and Preslav Nakov. 2020 · 2004
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Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2020 · 2006
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Early exit optimizations for additive machine learned ranking systems
B Barla Cambazoglu, Hugo Zaragoza, Olivier Chapelle, Jiang Chen, Ciya Liao, Zhaohui Zheng, and Jon Degenhardt. 2010 · 2010
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Ncbi disease corpus: a resource for disease name recognition and concept normalization
Rezarta Islamaj Doğan, Robert Leaman, and Zhiyong Lu. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Jimmy Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton. 2016 · 2016
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Improving neural language models with a continuous cache
Edouard Grave, Armand Joulin, and Nicolas Usunier. 2016 · 2016
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Chemprot-3.0: a global chemical biology diseases mapping
Jens Kringelum, Sonny Kim Kjaerulff, Søren Brunak, Ole Lund, Tudor I Oprea, and Olivier Taboureau. 2016 · 2016
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Biocreative v cdr task corpus: a resource for chemical disease relation extraction
Jiao Li, Yueping Sun, Robin J Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu. 2016 · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Freezeout: Accelerate training by progressively freezing layers
Andrew Brock, Theodore Lim, James M. Ritchie, and Nick Weston. 2017 · 2017
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Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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Svcca: Singular vector canonical correlation analysis for deep learning dynamics and interpretability
Maithra Raghu, Justin Gilmer, Jason Yosinski, and Jascha Sohl-Dickstein. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Do transformers need deep long-range memory?
Jack Rae and Ali Razavi. 2020 · 2020
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A primer in BERTology: What we know about how BERT works
Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2020 · 2020
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Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers
Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020 · 2020
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DeeBERT: Dynamic early exiting for accelerating BERT inference
Ji Xin, Raphael Tang, Jaejun Lee, Yaoliang Yu, and Jimmy Lin. 2020 · 2020
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Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018 · 2018
Cited alongside, same era.
Insights on representational similarity in neural networks with canonical correlation
Ari Morcos, Maithra Raghu, and Samy Bengio. 2018 · 2018
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
Cited alongside, same era.
SciBERT: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
Cited alongside, same era.
Structural scaffolds for citation intent classification in scientific publications
Arman Cohan, Waleed Ammar, Madeleine van Zuylen, and Field Cady. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
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 · 2019
Cited alongside, same era.
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. 2021 · 2021
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A dataset of information-seeking questions and answers anchored in research papers
Pradeep Dasigi, Kyle Lo, Iz Beltagy, Arman Cohan, Noah A. Smith, and Matt Gardner. 2021 · 2021
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Pipetransformer: automated elastic pipelining for distributed training of large-scale models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, and Salman Avestimehr. 2021 · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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ReadOnce transformers: Reusable representations of text for transformers
Shih-Ting Lin, Ashish Sabharwal, and Tushar Khot. 2021 · 2021
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Autofreeze: Automatically freezing model blocks to accelerate fine-tuning
Yuhan Liu, Saurabh Agarwal, and Shivaram Venkataraman. 2021 · 2021
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Adapterdrop: On the efficiency of adapters in transformers
Andreas Rücklé, Gregor Geigle, Max Glockner, Tilman Beck, Jonas Pfeiffer, Nils Reimers, and Iryna Gurevych. 2021 · 2021
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MiniLMv2: Multi-head self-attention relation distillation for compressing pretrained transformers
Wenhui Wang, Hangbo Bao, Shaohan Huang, Li Dong, and Furu Wei. 2021 · 2021
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Delta tuning: A comprehensive study of parameter efficient methods for pre-trained language models
Ning Ding, Yujia Qin, Guang Yang, Fuchao Wei, Zonghan Yang, Yusheng Su, Shengding Hu, Yulin Chen, Chi-Min Chan, Weize Chen, et al. 2022 · 2022
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Measuring the carbon intensity of ai in cloud instances
Jesse Dodge, Taylor Prewitt, Remi Tachet des Combes, Erika Odmark, Roy Schwartz, Emma Strubell, Alexandra Sasha Luccioni, Noah A Smith, Nicole DeCario, and Will Buchanan. 2022 · 2022
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Prompt-free and efficient few-shot learning with language models
Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson, Lambert Mathias, Marzieh Saeidi, Veselin Stoyanov, and Majid Yazdani. 2022 · 2022
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Skipbert: Efficient inference with shallow layer skipping
Jue Wang, Ke Chen, Gang Chen, Lidan Shou, and Julian McAuley. 2022 · 2022
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A flexible multi-task model for bert serving
Tianwen Wei, Jianwei Qi, and Shenghuang He. 2022 · 2022
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Yuhuai Wu, Markus N Rabe, DeLesley Hutchins, and Christian Szegedy. 2022 · 2022
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Linkbert: Pretraining language models with document links
Michihiro Yasunaga, Jure Leskovec, and Percy Liang. 2022 · 2022
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