A glance at in-context learning

Yongliang WU , Xu YANG

Front. Comput. Sci. ›› 2024, Vol. 18 ›› Issue (5) : 185347

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Front. Comput. Sci. ›› 2024, Vol. 18 ›› Issue (5) : 185347 DOI: 10.1007/s11704-024-40013-9
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A glance at in-context learning

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Yongliang WU, Xu YANG. A glance at in-context learning. Front. Comput. Sci., 2024, 18(5): 185347 DOI:10.1007/s11704-024-40013-9

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References

[1]

Radford A, Kim J W, Hallacy C, Ramesh A, Goh G, Agarwal S, Sastry G, Askell A, Mishkin P, Clark J, Krueger G, Sutskever I. Learning transferable visual models from natural language supervision. In: Proceedings of the 38th International Conference on Machine Learning. 2021, 8748−8763

[2]

Sun K, Luo X, Luo M Y. A survey of pretrained language models. In: Proceedings of International Conference on Knowledge Science, Engineering and Management. 2022, 442−456

[3]

Brown T B, Mann B, Ryder N, Subbiah M, Kaplan J D, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A, Agarwal S, Herbert-Voss A, Krueger G, Henighan T, Child R, Ramesh A, Ziegler D M, Wu J, Winter C, Hesse C, Chen M, Sigler E, Litwin M, Gray S, Chess B, Clark J, Berner C, McCandlish S, Radford A, Sutskever I, Amodei D. Language models are few-shot learners. In: Proceedings of the 34th International Conference on Neural Information Processing Systems. 2020, 159

[4]

Hofstadter D R, Sander E. Surfaces and Essences: Analogy as the Fuel and Fire of Thinking. New York: Basic Books, 2013

[5]

Wen M, Lin R, Wang H, Yang Y, Wen Y, Mai L, Wang J, Zhang H, Zhang W. Large sequence models for sequential decision-making: a survey. Frontiers of Computer Science, 2023, 17( 6): 176349

[6]

Xie S M, Raghunathan A, Liang P, Ma T. An explanation of in-context learning as implicit Bayesian inference. In: Proceedings of the 10th International Conference on Learning Representations. 2021

[7]

Yang X, Wu Y, Yang M, Chen H, Geng X. Exploring diverse in-context configurations for image captioning. In: Proceedings of the 37th Conference on Neural Information Processing Systems. 2024

[8]

Wang L, Li L, Dai D, Chen D, Zhou H, Meng F, Zhou J, Sun X. Label words are anchors: An information flow perspective for understanding in-context learning. In: Proceedings of 2023 Conference on Empirical Methods in Natural Language Processing. 2023, 9840−9855

[9]

Achiam J, Adler S, Agarwal S, Ahmad L, Akkaya I, Aleman F L, Almeida D, Altenschmidt J, Altman S, Anadkat S, others. Gpt-4 Technical Report. 2023, arXiv preprint arXiv:2303.08774

[10]

Li L, Peng J, Chen H, Gao C, Yang X. How to configure good in-context sequence for visual question answering. 2023, arXiv preprint arXiv: 2312.01571

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