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GPT-HateCheck: Can LLMs Write Better Functional Tests for Hate Speech Detection?

, , and . LREC/COLING, page 7867-7885. ELRA and ICCL, (2024)

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Bridging the Gap Between Research and Production with CODE., , and . PAKDD (3), volume 11441 of Lecture Notes in Computer Science, page 277-288. Springer, (2019)ARAIDA: Analogical Reasoning-Augmented Interactive Data Annotation., , , , and . CoRR, (2024)Mining Scientific Terms and their Definitions: A Study of the ACL Anthology., , , and . EMNLP, page 780-790. ACL, (2013)Combining Lightly-Supervised Text Classification Models for Accurate Contextual Advertising., , and . IJCNLP(1), page 545-554. Asian Federation of Natural Language Processing, (2017)Genre-Oriented Web Content Extraction with Deep Convolutional Neural Networks and Statistical Methods., , , and . PACLIC, Association for Computational Linguistics, (2018)GPT-HateCheck: Can LLMs Write Better Functional Tests for Hate Speech Detection?, , and . LREC/COLING, page 7867-7885. ELRA and ICCL, (2024)Learning Only from Relevant Keywords and Unlabeled Documents., , , , and . EMNLP/IJCNLP (1), page 3991-4000. Association for Computational Linguistics, (2019)Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods., and . INLG, page 133-142. The Association for Computer Linguistics, (2016)Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation., , and . NAACL-HLT (Student Research Workshop), page 112-118. Association for Computational Linguistics, (2021)