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Existing large language models (LLMs) can only afford fix-sized inputs due to the input length limit, preventing them from utilizing rich long-context information from past inputs.
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Dbpedia: A nucleus for a web of open data
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Adam: A method for stochastic optimization
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Improving language understanding with unsupervised learning
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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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
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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 · 2019
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Compressive transformers for long-range sequence modelling
Jack W Rae, Anna Potapenko, Siddhant M Jayakumar, and Timothy P Lillicrap · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le · 2019
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
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Aurko Roy, Mohammad Saffar, Ashish Vaswani, and David Grangier · 2021
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Lst: Ladder side-tuning for parameter and memory efficient transfer learning
Yi-Lin Sung, Jaemin Cho, and Mohit Bansal · 2022
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al · 2022
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Chapterbreak: A challenge dataset for long-range language models
Simeng Sun, Katherine Thai, and Mohit Iyyer · 2022
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Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam M. Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z Li, Madian Khabsa, Han Fang, and Hao Ma · 2020
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, et al · 2020
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Side-tuning: a baseline for network adaptation via additive side networks
Jeffrey O Zhang, Alexander Sax, Amir Zamir, Leonidas Guibas, and Jitendra Malik · 2020
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Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, T. W. Hennigan, Saffron Huang, Lorenzo Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, and L. Sifre · 2021
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Train short, test long: Attention with linear biases enables input length extrapolation
Ofir Press, Noah A Smith, and Mike Lewis · 2021
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Emergent abilities of large language models
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Chain of thought prompting elicits reasoning in large language models
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Task-oriented dialogue system as natural language generation
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Opt: Open pre-trained transformer language models
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N-gram nearest neighbor machine translation
Rui Lv, Junliang Guo, Rui Wang, Xu Tan, Qi Liu, and Tao Qin · 2023
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