ScholarGate
Msaidizi
Process / pipeline

Uainishaji wa maandishi kwa michache ya mifano (Few-Shot Text Classification)

Uainishaji wa maandishi kwa michache ya mifano huweka hati katika madaraja kwa kutumia mifano michache tu iliyoandikwa kwa kila daraja. Kwa kuanzia na maendeleo ya Gao et al. (2021) na mbinu ya SetFit isiyo na kidokezo ya Tunstall et al. (2022), inategemea mitandao ya kiini (prototypical networks), MAML, au urekebishaji wa mfumo mkuu uliotangulia kufunzwa ili kujifunza kutoka kwa lebo chache.

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Vyanzo

  1. Gao, T., Fisch, A. & Chen, D. (2021). Making Pre-trained Language Models Better Few-shot Learners. ACL. DOI: 10.18653/v1/2021.acl-long.295
  2. Tunstall, L., Reimers, N., Jo, U.E.S., Bates, L., Korat, D., Wasserblat, M. & Pereg, O. (2022). Efficient Few-Shot Learning Without Prompts. arXiv. DOI: 10.48550/arXiv.2209.11055

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 1). Few-Shot Text Classification. ScholarGate. https://scholargate.app/sw/text-mining/few-shot-text-classification

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Imerejelewa na

ScholarGateFew-Shot Text Classification (Few-Shot Text Classification). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/text-mining/few-shot-text-classification · Seti ya data: https://doi.org/10.5281/zenodo.20539026