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Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models

, and . Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, page 11987--12004. Miami, Florida, USA, Association for Computational Linguistics, (November 2024)

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An Overview of Canonical Text Services, and . Linguistics and Literature Studies, (March 2017)Mining Big Data With Computational Methods, , , , and . page 201--217. (January 2016)The Canonical Text Services in Classics and Beyond, and . page 95--114. (August 2019)A big data case study in digital humanities, and . Datenbank Spektrum, 19 (1): 41--49 (March 2019)On Classifying whether Two Texts are on the Same Side of an Argument, , , , and . Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, page 10130–10138. Association for Computational Linguistics, (2021)Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models, and . Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, page 11987--12004. Miami, Florida, USA, Association for Computational Linguistics, (November 2024)Casting the Same Sentiment Classification Problem, , , and . Findings of the Association for Computational Linguistics: EMNLP 2021, Association for Computational Linguistics, (2021)Same Side Stance Classification Using Contextualized Sentence Embeddings, , and . (August 2019)Case study: Preparing a TEI corpus for Canonical Text Services. (2016)Visualisierungen für CTS Text Miner. (2016)