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There is great interest in fine-tuning frontier large language models (LLMs) to inject new information and update existing knowledge.
Knowledge infusion
Leslie G Valiant · 2006
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Anne Lauscher, Olga Majewska, Leonardo FR Ribeiro, Iryna Gurevych, Nikolai Rozanov, and Goran Glavaš · 2020
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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
Earlier work this paper cites.
K-adapter: Infusing knowledge into pre-trained models with adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Guihong Cao, Daxin Jiang, Ming Zhou, et al · 2020
Earlier work this paper cites.
Fine-tuning gpt-3 for russian text summarization
Nikolich Alexandr, Osliakova Irina, Kudinova Tatyana, Kappusheva Inessa, and Puchkova Arina · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Earlier work this paper cites.
Instructeval: Towards holistic evaluation of instruction-tuned large language models
Yew Ken Chia, Pengfei Hong, Lidong Bing, and Soujanya Poria · 2023
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Fine-tuning gpt-3 for legal rule classification
Davide Liga and Livio Robaldo · 2023
Cited alongside, same era.
Orca 2: Teaching small language models how to reason
Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Clarisse Simoes, Sahaj Agarwal, Xuxi Chen, Anastasia Razdaibiedina, Erik Jones, Kriti Aggarwal, et al · 2023
Cited alongside, same era.
Fine-tuning or retrieval? comparing knowledge injection in llms
Oded Ovadia, Menachem Brief, Moshik Mishaeli, and Oren Elisha · 2023
Cited alongside, same era.
Does fine-tuning gpt-3 with the openai api leak personally-identifiable information?
Albert Yu Sun, Eliott Zemour, Arushi Saxena, Udith Vaidyanathan, Eric Lin, Christian Lau, and Vaikkunth Mugunthan · 2023
Cited alongside, same era.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al · 2024
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Some doctors are using public ai chatbots like chatgpt in clinical decisions. is it safe?, Oct 2024
Anastassia Gliadkovskaya · 2024
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Ai writes over 25
Jack Kelly · 2024
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Fine-tuning chatgpt for automatic scoring
Ehsan Latif and Xiaoming Zhai · 2024
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Table-gpt: Table fine-tuned gpt for diverse table tasks
Peng Li, Yeye He, Dror Yashar, Weiwei Cui, Song Ge, Haidong Zhang, Danielle Rifinski Fainman, Dongmei Zhang, and Surajit Chaudhuri · 2024
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Fine-tuning gpt-3 for machine learning electronic and functional properties of organic molecules
Zikai Xie, Xenophon Evangelopoulos, Ömer H Omar, Alessandro Troisi, Andrew I Cooper, and Linjiang Chen · 2024
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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.
Removing rlhf protections in gpt-4 via fine-tuning
Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, and Daniel Kang · 2023
Cited alongside, same era.
Fine-tuning gpt on biomedical nlp tasks: an empirical evaluation
Hamza Bousselham, Asmaa Mourhir, et al · 2024
Cited alongside, same era.
Llama slayer 8b: Shallow layers hold the key to knowledge injection
Tianxiang Chen, Zhentao Tan, Tao Gong, Yue Wu, Qi Chu, Bin Liu, Jieping Ye, and Nenghai Yu · 2024
Cited alongside, same era.
How well do llms cite relevant medical references? an evaluation framework and analyses
Kevin Wu, Eric Wu, Ally Cassasola, Angela Zhang, Kevin Wei, Teresa Nguyen, Sith Riantawan, Patricia Shi Riantawan, Daniel E Ho, and James Zou
Cited in the paper.
Clasheval: Quantifying the tug-of-war between an llm’s internal prior and external evidence
Kevin Wu, Eric Wu, and James Zou
Cited in the paper.
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Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al · 2024
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