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Machine learningDeep learning / NLP / CV

Transferlæring med tekstresumégenerering

Transferlæring med tekstresumégenerering tilpasser en stor sprogmodel, der er forhåndstrænet på brede tekstkorpora – såsom T5, BART eller PEGASUS – til opgaven med at kondensere dokumenter til kortere, sammenhængende resuméer. Ved at genbruge indlært sproglig viden og finjustere på domænespecifikke par af kildedokumenter og referenceresuméer opnår denne tilgang en stærk resumégenereringskvalitet med beskedne krav til mærkede data.

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Kilder

  1. Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020). Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of Machine Learning Research, 21(140), 1–67. link
  2. Lewis, M., Liu, Y., Goyal, N., Ghahravi, M., Mohamed, A., Chen, D., Levy, O., & Zettlemoyer, L. (2020). BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 7871–7880). ACL. DOI: 10.18653/v1/2020.acl-main.703

Sådan citerer du denne side

ScholarGate. (2026, June 3). Transfer Learning with Neural Text Summarization. ScholarGate. https://scholargate.app/da/deep-learning/transfer-learning-with-text-summarization

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Refereret af

ScholarGateTransfer Learning with Text Summarization (Transfer Learning with Neural Text Summarization). Hentet 2026-06-15 fra https://scholargate.app/da/deep-learning/transfer-learning-with-text-summarization · Datasæt: https://doi.org/10.5281/zenodo.20539026