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Learning Transferable Visual Models From Natural Language Supervision

Radford et al. · 2021 · Proceedings of ICML 2021

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Methods survey: emerging mathematics and machine learning	SRC0D8NJCBP11SK
Survey: inductive methods from fourteen fields	SRC0D8NJDAY13ME

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Radford, A., Kim, J., Hallacy, C. et al. 2021. Learning Transferable Visual Models From Natural Language Supervision. Proceedings of ICML 2021.

@article{radford2021learning,
  author = {Radford, Alec and Kim, Jong Wook and Hallacy, Chris and Ramesh, Aditya and Goh, Gabriel and Agarwal, Sandhini and Sastry, Girish and Askell, Amanda and Mishkin, Pamela and Clark, Jack and Krueger, Gretchen and Sutskever, Ilya},
  title = {Learning Transferable Visual Models From Natural Language Supervision},
  journal = {Proceedings of ICML 2021},
  year = {2021},
  url = {https://arxiv.org/abs/2103.00020}
}

Web: https://arxiv.org/abs/2103.00020
Licence: arXiv-nonexclusive
Cite key: radford2021learning
SHA-256: 6478b6e571a7d6fcd846d8ef77bfd60c285f1986abb8f475eedc43de403074f5

In the research Session 6: Phase 2: registered tests, brute force, five surveys; book v1.1ConsultedSession 9: The inquiry framework, the inductive battery, generated hypotheses and readingsConsulted

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v1 · 25 Oct 2026 · Voynich Manuscript: sync from the research ledger