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Fine-tuning large language models (LLMs) is essential for enhancing their performance on specific tasks but is often resource-intensive due to redundant or uninformative data.
An analysis of approximations for maximizing submodular set functions—i
George L. Nemhauser, Laurence A. Wolsey, and Marshall L. Fisher · 1978
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Chin-Yew Lin · 2004
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Submodular functions and optimization
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Language models are few-shot learners
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Training verifiers to solve math word problems, 2021
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Measuring massive multitask language understanding
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Submodular combinatorial information measures with applications in machine learning
Rishabh Iyer, Ninad Khargoankar, Jeff Bilmes, and Himanshu Asanani · 2021
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Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, and Alexander M. Rush · 2021
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Finetuned language models are zero-shot learners
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Llama: Open and efficient foundation language models, 2023
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
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C-pack: Packaged resources to advance general chinese embedding, 2023
Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena, 2023
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Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V Le · 2022
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Qianlong Du, Chengqing Zong, and Jiajun Zhang · 2023
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Dongfu Jiang, Xiang Ren, and Bill Yuchen Lin · 2023
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Milo: Model-agnostic subset selection framework for efficient model training and tuning, 2023
Krishnateja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati, Kiran Kate, Lucian Popa, and Rishabh Iyer · 2023
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Prometheus: Inducing fine-grained evaluation capability in language models
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The flan collection: designing data and methods for effective instruction tuning
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Grad-match: Gradient matching based data subset selection for efficient deep model training, 2021a
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