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Large language models (LLMs) with one or more fine-tuning phases have become a necessary step to unlock various capabilities, enabling LLMs to follow natural language instructions or align with human preferences.
Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning · 2018
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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
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne · 2019
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Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting
Xilai Li, Yingbo Zhou, Tianfu Wu, Richard Socher, and Caiming Xiong · 2019
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al · 2019
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Episodic memory reader: Learning what to remember for question answering from streaming data
Moonsu Han, Minki Kang, Hyunwoo Jung, and Sung Ju Hwang · 2019
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How fine can fine-tuning be? learning efficient language models
Evani Radiya-Dixit and Xin Wang · 2020
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Tydi qa: A benchmark for information-seeking question answering in ty pologically di verse languages
Jonathan H Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki · 2020
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Parameter-efficient multi-task fine-tuning for transformers via shared hypernetworks
Rabeeh Karimi Mahabadi, Sebastian Ruder, Mostafa Dehghani, and James Henderson · 2021
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Parameter-efficient transfer learning with diff pruning
Demi Guo, Alexander Rush, and Yoon Kim · 2021
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Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models
Elad Ben Zaken, Shauli Ravfogel, and Yoav Goldberg · 2021
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2021
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
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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, et al · 2021
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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On the effectiveness of parameter-efficient fine-tuning, 2022
Zihao Fu, Haoran Yang, Anthony Man-Cho So, Wai Lam, Lidong Bing, and Nigel Collier · 2022
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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
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Nispa: Neuro-inspired stability-plasticity adaptation for continual learning in sparse networks
Mustafa B Gurbuz and Constantine Dovrolis · 2022
Cited alongside, same era.
Super-NaturalInstructions: Generalization via declarative instructions on 1600+ NLP tasks
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Atharva Naik, Arjun Ashok, Arut Selvan Dhanasekaran, Anjana Arunkumar, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Kuntal Kumar Pal, Maitreya Patel, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Savan Doshi, Shailaja Keyur Sampat, Siddhartha Mishra, Sujan Reddy A, Sumanta Patro, Tanay Dixit, and Xudong Shen · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
TruthfulQA: Measuring how models mimic human falsehoods
Lm-cocktail: Resilient tuning of language models via model merging
Shitao Xiao, Zheng Liu, Peitian Zhang, and Xingrun Xing · 2023
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An empirical study of catastrophic forgetting in large language models during continual fine-tuning
Yun Luo, Zhen Yang, Fandong Meng, Yafu Li, Jie Zhou, and Yue Zhang · 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
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Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023
Mike Conover, Matt Hayes, Ankit Mathur, Xiangrui Meng, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, et al · 2023
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Stanford alpaca: An instruction-following llama model, 2023
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Stephanie Lin, Jacob Hilton, and Owain Evans · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Cited alongside, same era.
Disentqa: Disentangling parametric and contextual knowledge with counterfactual question answering
Ella Neeman, Roee Aharoni, Or Honovich, Leshem Choshen, Idan Szpektor, and Omri Abend · 2023
Cited alongside, same era.
Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Jun Zhao, Wei Shen, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Xiaoran Fan, et al · 2023
Cited alongside, same era.
Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi · 2023
Cited alongside, same era.
Ties-merging: Resolving interference when merging models
Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, and Mohit Bansal · 2023
Cited alongside, same era.
Language models are super mario: Absorbing abilities from homologous models as a free lunch
Le Yu, Bowen Yu, Haiyang Yu, Fei Huang, and Yongbin Li · 2023
Cited alongside, same era.
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto · 2023
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Baize: An open-source chat model with parameter-efficient tuning on self-chat data
Canwen Xu, Daya Guo, Nan Duan, and Julian McAuley · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al · 2023
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Code alpaca: An instruction-following llama model for code generation, 2023
Sahil Chaudhary · 2023
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Challenging BIG-bench tasks and whether chain-of-thought can solve them
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc Le, Ed Chi, Denny Zhou, and Jason Wei · 2023
Later among the works it cites.
Alpacaeval: An automatic evaluator of instruction-following models
Xuechen Li, Tianyi Zhang, Yann Dubois, Rohan Taori, Ishaan Gulrajani, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto · 2023
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The unlocking spell on base LLMs: Rethinking alignment via in-context learning
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Chandu, Chandra Bhagavatula, and Yejin Choi · 2024
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How abilities in large language models are affected by supervised fine-tuning data composition, 2024
Guanting Dong, Hongyi Yuan, Keming Lu, Chengpeng Li, Mingfeng Xue, Dayiheng Liu, Wei Wang, Zheng Yuan, Chang Zhou, and Jingren Zhou · 2024
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Parameter-efficient fine-tuning for large models: A comprehensive survey
Zeyu Han, Chao Gao, Jinyang Liu, Sai Qian Zhang, et al · 2024
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2024
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A comprehensive survey of continual learning: Theory, method and application
Liyuan Wang, Xingxing Zhang, Hang Su, and Jun Zhu · 2024
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Scalable language model with generalized continual learning
Bohao Peng, Zhuotao Tian, Shu Liu, Mingchang Yang, and Jiaya Jia · 2024
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Openassistant conversations-democratizing large language model alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, et al · 2024
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