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Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of Large Language Models (LLMs) to various downstream applications.
Zero-shot relation extraction via reading comprehension
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Parameter-efficient transfer learning for NLP
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Natural questions: a benchmark for question answering research
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Lora: Low-rank adaptation of large language models
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Plug-and-play adaptation for continuously-updated QA
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Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin Raffel. 2022 · 2022
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Crosslingual generalization through multitask finetuning
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Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
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Large language models with controllable working memory
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Scaling down to scale up: A guide to parameter-efficient fine-tuning
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Empirical analysis of the strengths and weaknesses of PEFT techniques for llms
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Infodiffusion: Information entropy aware diffusion process for non-autoregressive text generation
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Editing large language models: Problems, methods, and opportunities
Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, and Ningyu Zhang. 2023 · 2023
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Adaptive budget allocation for parameter-efficient fine-tuning
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A survey of large language models
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Can we edit factual knowledge by in-context learning?
Ce Zheng, Lei Li, Qingxiu Dong, Yuxuan Fan, Zhiyong Wu, Jingjing Xu, and Baobao Chang. 2023 · 2023
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A comprehensive study of knowledge editing for large language models
Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, Siyuan Cheng, Ziwen Xu, Xin Xu, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, and Huajun Chen. 2024 · 2024
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