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Language models (LMs) exhibit impressive performance and generalization capabilities.
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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Roberta: A robustly optimized bert pretraining approach
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Winogrande: An adversarial winograd schema challenge at scale
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Catastrophic interference in connectionist networks: The sequential learning problem
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Learning capability and storage capacity of two-hidden-layer feedforward networks
Guang-Bin Huang. 2003 · 2003
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Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara. 2020 · 2004
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Mining and summarizing customer reviews
Minqing Hu and Bing Liu. 2004 · 2004
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A holistic lexicon-based approach to opinion mining
Xiaowen Ding, Bing Liu, and Philip S Yu. 2008 · 2008
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Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Chemprot-3.0: a global chemical biology diseases mapping
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Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence , page 556–572
Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, and Philip H. S. Torr. 2018 · 2018
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
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Measuring the evolution of a scientific field through citation frames
David Jurgens, Srijan Kumar, Raine Hoover, Daniel A. McFarland, and Dan Jurafsky. 2018 · 2018
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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
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà, Didac Suris, Marius Miron, and Alexandros Karatzoglou. 2018 · 2018
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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
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Episodic memory in lifelong language learning
Cyprien de Masson D’Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama. 2019 · 2019
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin. 2019 · 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 · 2019
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Justifying recommendations using distantly-labeled reviews and fine-grained aspects
Jianmo Ni, Jiacheng Li, and Julian J. McAuley. 2019 · 2019
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BERT post-training for review reading comprehension and aspect-based sentiment analysis
Hu Xu, Bing Liu, Lei Shu, and Philip S. Yu. 2019 · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Wizardcoder: Empowering code large language models with evol-instruct
Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, and Daxin Jiang. 2023 · 2023
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Zihan Qiu, Zeyu Huang, and Jie Fu. 2023 · 2023
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Progressive prompts: Continual learning for language models
Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, and Amjad Almahairi. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Orthogonal subspace learning for language model continual learning
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S2ORC: the semantic scholar open research corpus
Kyle Lo, Lucy Lu Wang, Mark Neumann, Rodney Kinney, and Daniel S. Weld. 2020 · 2020
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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. 2020 · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021 · 2021
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Demix layers: Disentangling domains for modular language modeling
Suchin Gururangan, Mike Lewis, Ari Holtzman, Noah A Smith, and Luke Zettlemoyer. 2021 · 2021
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Adapting bert for continual learning of a sequence of aspect sentiment classification tasks
Zixuan Ke, Hu Xu, and Bing Liu. 2021 · 2021
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Lfpt5: A unified framework for lifelong few-shot language learning based on prompt tuning of t5
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LoRA: Low-rank adaptation of large language models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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Xiao Wang, Tianze Chen, Qiming Ge, Han Xia, Rong Bao, Rui Zheng, Qi Zhang, Tao Gui, and Xuan-Jing Huang. 2023b · 2023
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Learn or recall? revisiting incremental learning with pre-trained language models
Junhao Zheng, Shengjie Qiu, and Qianli Ma. 2023 · 2023
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A survey on model compression for large language models
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Scaling sparse fine-tuning to large language models
Alan Ansell, Ivan Vulić, Hannah Sterz, Anna Korhonen, and Edoardo M. Ponti. 2024 · 2024
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Lora learns less and forgets less
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Unlocking emergent modularity in large language models
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Continual learning of large language models: A comprehensive survey
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Turbo sparse: Achieving llm sota performance with minimal activated parameters
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