PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration - ACL Anthology

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PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration

Minseok Choi, Hyesu Lim, Jaegul Choo

Anthology ID:: 2023.findings-ijcnlp.4
Volume:: Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings)
Month:: November
Year:: 2023
Address:: Nusa Dua, Bali
Editors:: Jong C. Park, Yuki Arase, Baotian Hu, Wei Lu, Derry Wijaya, Ayu Purwarianti, Adila Alfa Krisnadhi
Venue:: Findings
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 39–47
Language:
URL:: https://aclanthology.org/2023.findings-ijcnlp.4
DOI:: 10.18653/v1/2023.findings-ijcnlp.4
Bibkey:
Cite (ACL):: Minseok Choi, Hyesu Lim, and Jaegul Choo. 2023. PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration. In Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings), pages 39–47, Nusa Dua, Bali. Association for Computational Linguistics.
Cite (Informal):: PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration (Choi et al., Findings 2023)
Copy Citation:
PDF:: https://preview.aclanthology.org/ingest-2024-clasp/2023.findings-ijcnlp.4.pdf