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The complexity and sheer volume of information encompassing documents, papers, data, and other resources from large-scale experiments demand significant time and effort to navigate, making the task of accessing and utilizing these varied forms of information daunting, particularly for new collaborators and early-career scientists.
Retrieval-augmented generation for knowledge-intensive nlp tasks, 2021
P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W. tau Yih, T. Rocktäschel, S. Riedel, and D. Kiela · 2005
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Efficient estimation of word representations in vector space, 2013
T. Mikolov, K. Chen, G. Corrado, and J. Dean · 2013
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Language models are few-shot learners, 2020
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei · 2020
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How to fine-tune bert for text classification?, 2020
C. Sun, X. Qiu, Y. Xu, and X. Huang · 2020
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Science requirements and detector concepts for the electron-ion collider: Eic yellow report
R. Abdul Khalek, A. Accardi, and et. al · 2022
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Langchain, 2022
C. Harisson · 2022
Cited alongside, same era.
Self-rag: Learning to retrieve, generate, and critique through self-reflection, 2023
A. Asai, Z. Wu, Y. Wang, A. Sil, and H. Hajishirzi · 2023
Cited alongside, same era.
A survey on in-context learning, 2023
Q. Dong, L. Li, D. Dai, C. Zheng, Z. Wu, B. Chang, X. Sun, J. Xu, L. Li, and Z. Sui · 2023
Cited alongside, same era.
Ragas: Automated evaluation of retrieval augmented generation, 2023
S. Es, J. James, L. Espinosa-Anke, and S. Schockaert · 2023
Cited alongside, same era.
Fine-tuning transformers: Vocabulary transfer
V. Mosin, I. Samenko, B. Kozlovskii, A. Tikhonov, and I. P. Yamshchikov · 2023
Later among the works it cites.
ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope
P. P. Ray · 2023
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Llama 2: Open foundation and fine-tuned chat models, 2023
H. Touvron et al · 2023
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Retrieval-augmented generation for large language models: A survey, 2024
Y. Gao, Y. Xiong, X. Gao, K. Jia, J. Pan, Y. Bi, Y. Dai, J. Sun, Q. Guo, M. Wang, and H. Wang · 2024
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