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Recent work has improved language models (LMs) remarkably by equipping them with a non-parametric memory component.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Generating long sequences with sparse Transformers
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever. 2019 · 1904
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BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Longformer: The long-document Transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun. 2006 · 2006
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z Li, Madian Khabsa, Han Fang, and Hao Ma. 2020 · 2006
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Rethinking attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, et al. 2020 · 2009
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Large text compression benchmark
Matt Mahoney. 2009 · 2009
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The probabilistic relevance framework: BM25 and beyond
Stephen Robertson and Hugo Zaragoza. 2009 · 2009
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Efficient Transformers: A survey
Yi Tay, Mostafa Dehghani, Dara Bahri, and Donald Metzler. 2020 · 2009
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Earlier work this paper cites.
Ask me anything: Dynamic memory networks for natural language processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, and Richard Socher. 2016 · 2016
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 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 · 2017
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Generating Wikipedia by summarizing long sequences
Peter J Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Character-level language modeling with deeper self-attention
Rami Al-Rfou, Dokook Choe, Noah Constant, Mandy Guo, and Llion Jones. 2019 · 2019
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Adaptive input representations for neural language modeling
Alexei Baevski and Michael Auli. 2019 · 2019
Cited alongside, same era.
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 · 2019
Cited alongside, same era.
Episodic memory in lifelong language learning
Cyprien de Masson D’Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama. 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.
Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2019 · 2019
Cited alongside, same era.
fairseq: A fast, extensible toolkit for sequence modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli. 2019 · 2019
Nearest neighbor machine translation
Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2021 · 2021
Later among the works it cites.
When attention meets fast recurrence: Training language models with reduced compute
Tao Lei. 2021 · 2021
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Random feature attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A Smith, and Lingpeng Kong. 2021 · 2021
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KILT: a benchmark for knowledge intensive language tasks
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, et al. 2021 · 2021
Later among the works it cites.
End-to-end training of multi-document reader and retriever for open-domain question answering
Devendra Singh, Siva Reddy, Will Hamilton, Chris Dyer, and Dani Yogatama. 2021 · 2021
Later among the works it cites.
Not all memories are created equal: Learning to forget by expiring
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Cited alongside, same era.
Adaptive attention span in Transformers
Sainbayar Sukhbaatar, Édouard Grave, Piotr Bojanowski, and Armand Joulin. 2019 · 2019
Cited alongside, same era.
REALM: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Cited alongside, same era.
Transformers are RNNs: Fast autoregressive Transformers with linear attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, and François Fleuret. 2020 · 2020
Cited alongside, same era.
Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2020 · 2020
Cited alongside, same era.
Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al. 2020 · 2020
Cited alongside, same era.
Sainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, and Angela Fan. 2021 · 2021
Later among the works it cites.
Adaptive semiparametric language models
Dani Yogatama, Cyprien de Masson d’Autume, and Lingpeng Kong. 2021 · 2021
Later among the works it cites.
Readtwice: Reading very large documents with memories
Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, and Fei Sha. 2021 · 2021
Later among the works it cites.
Adaptive nearest neighbor machine translation
Xin Zheng, Zhirui Zhang, Junliang Guo, Shujian Huang, Boxing Chen, Weihua Luo, and Jiajun Chen. 2021 · 2021
Later among the works it cites.
Augmenting pre-trained language models with qa-memory for open-domain question answering
Wenhu Chen, Pat Verga, Michiel de Jong, John Wieting, and William Cohen. 2022 · 2022
Closest in time.
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 · 2022
Closest in time.
Mention memory: incorporating textual knowledge into transformers through entity mention attention
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, and William Cohen. 2022 · 2022
Closest in time.
LaMemo: Language modeling with look-ahead memory
Haozhe Ji, Rongsheng Zhang, Zhenyu Yang, Zhipeng Hu, and Minlie Huang. 2022 · 2022
Closest in time.
∞ \infty -former: Infinite memory Transformer
Pedro Henrique Martins, Zita Marinho, and André FT Martins. 2022 · 2022
Closest in time.
Gnn-lm: Language modeling based on global contexts via gnn
Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, and Jiwei Li. 2022 · 2022
Closest in time.
Memorizing Transformers
Yuhuai Wu, Markus N Rabe, DeLesley Hutchins, and Christian Szegedy. 2022 · 2022
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OPT: Open pre-trained Transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
Closest in time.