Filtros : "Financiamento IBM" "IEEE Transactions on Knowledge and Data Engineering" Limpar

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  • Fonte: IEEE Transactions on Knowledge and Data Engineering. Unidade: FFCLRP

    Assuntos: CIÊNCIA DA COMPUTAÇÃO, PROCESSAMENTO DE LINGUAGEM NATURAL, LINGUAGEM DE MÁQUINA

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    • ABNT

      LIU, Jiang et al. TKDP: threefold knowledge-enriched deep prompt tuning for few-shot named entity recognition. IEEE Transactions on Knowledge and Data Engineering, v. 36, n. 11, p. 6397-6409, 2024Tradução . . Disponível em: https://doi.org/10.1109/TKDE.2024.3389650. Acesso em: 09 nov. 2025.
    • APA

      Liu, J., Fei, H., Li, F., Li, J., Li, B., Liang, Z., et al. (2024). TKDP: threefold knowledge-enriched deep prompt tuning for few-shot named entity recognition. IEEE Transactions on Knowledge and Data Engineering, 36( 11), 6397-6409. doi:10.1109/TKDE.2024.3389650
    • NLM

      Liu J, Fei H, Li F, Li J, Li B, Liang Z, Teng C, Ji D. TKDP: threefold knowledge-enriched deep prompt tuning for few-shot named entity recognition [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2024 ; 36( 11): 6397-6409.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1109/TKDE.2024.3389650
    • Vancouver

      Liu J, Fei H, Li F, Li J, Li B, Liang Z, Teng C, Ji D. TKDP: threefold knowledge-enriched deep prompt tuning for few-shot named entity recognition [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2024 ; 36( 11): 6397-6409.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1109/TKDE.2024.3389650

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