Machine learningDeep learning / NLP / CV

Prilagođeno sažimanje teksta

Prilagođeno sažimanje teksta prilagođava veliki pred-obučen sekvenca-u-sekvencu model — kao što su BART, T5 ili PEGASUS — za generiranje sažetih sažetaka dokumenata treniranjem na parovima (dokument, sažetak) specifičnim za domenu. Pristup daje znatno fluentnije i vjernije sažetke od ekstraktivnih ili generičkih pristupa iskorištavanjem znanja kodiranog u milijardama pred-obučnih tokena.

Otvorite u MethodMindUskoroVideoUskoroDownload slides

Pročitajte cijelu metodu

Samo za članove

Prijavite se besplatnim računom kako biste pročitali ovaj odjeljak.

Prijavite se

Method map

The neighbourhood of related methods — select a node to explore.

+1 more

Izvori

  1. Zhang, J., Zhao, Y., Saleh, M., & Liu, P. J. (2020). PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization. Proceedings of the 37th International Conference on Machine Learning (ICML), 119, 11328–11339. link
  2. Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2020). BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), 7871–7880. DOI: 10.18653/v1/2020.acl-main.703

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Fine-Tuned Pre-trained Sequence-to-Sequence Model for Text Summarization. ScholarGate. https://scholargate.app/hr/deep-learning/fine-tuned-text-summarization

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

Citirana u

ScholarGateFine-Tuned Text Summarization (Fine-Tuned Pre-trained Sequence-to-Sequence Model for Text Summarization). Preuzeto 2026-06-15 s https://scholargate.app/hr/deep-learning/fine-tuned-text-summarization · Skup podataka: https://doi.org/10.5281/zenodo.20539026