Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets

Irina Bejan, Artem Sokolov, Katja Filippova. Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets. In Houda Bouamor, Juan Pino 0001, Kalika Bali, editors, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023. pages 10107-10121, Association for Computational Linguistics, 2023. [doi]

Abstract

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