Retrieval-Based Unsupervised Noisy Label Detection on Text Data

Author:

Liu Peiyang1ORCID,Yang Jinyu2ORCID,Wang Lin1ORCID,Wang Sen1ORCID,Hao Yunlai1ORCID,Bai Huihui1ORCID

Affiliation:

1. PX Securities, Shen Zhen, China

2. Shanxi Institute of Energy, JIn Zhong, China

Publisher

ACM

Reference42 articles.

1. Ehsan Amid , Manfred K. Warmuth , Rohan Anil , and Tomer Koren . 2019 . Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019 , NeurIPS 2019, December 8--14, 2019, Vancouver, BC, Canada, Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 14987--14996. https://proceedings. neurips.cc/paper/2019/hash/8cd7775f9129da8b5bf787a063d8426e-Abstract.html Ehsan Amid, Manfred K. Warmuth, Rohan Anil, and Tomer Koren. 2019. Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8--14, 2019, Vancouver, BC, Canada, Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 14987--14996. https://proceedings. neurips.cc/paper/2019/hash/8cd7775f9129da8b5bf787a063d8426e-Abstract.html

2. Dara Bahri , Heinrich Jiang , and Maya R. Gupta . 2020. Deep k-NN for Noisy Labels . In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13--18 July 2020 , Virtual Event (Proceedings of Machine Learning Research , Vol. 119). PMLR, 540-- 550 . http://proceedings.mlr.press/v119/bahri20a.html Dara Bahri, Heinrich Jiang, and Maya R. Gupta. 2020. Deep k-NN for Noisy Labels. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13--18 July 2020, Virtual Event (Proceedings of Machine Learning Research, Vol. 119). PMLR, 540--550. http://proceedings.mlr.press/v119/bahri20a.html

3. Pengfei Chen , Benben Liao , Guangyong Chen , and Shengyu Zhang . 2019 . Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels . In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9--15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research , Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 1062-- 1070 . http://proceedings.mlr.press/v97/chen19g.html Pengfei Chen, Benben Liao, Guangyong Chen, and Shengyu Zhang. 2019. Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9--15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 1062--1070. http://proceedings.mlr.press/v97/chen19g.html

4. Hao Cheng , Zhaowei Zhu , Xingyu Li , Yifei Gong , Xing Sun , and Yang Liu . 2021 . Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. In 9th International Conference on Learning Representations, ICLR 2021 , Virtual Event, Austria, May 3--7 , 2021. OpenReview.net. https://openreview.net/forum?id=2VXyy9mIyU3 Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, and Yang Liu. 2021. Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3--7, 2021. OpenReview.net. https://openreview.net/forum?id=2VXyy9mIyU3

5. Derek Chong , Jenny Hong , and Christopher D. Manning . 2022. Detecting Label Errors by Using Pre-Trained Language Models . In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7--11, 2022 , Yoav Goldberg, Zornitsa Kozareva, and Yue Zhang (Eds.). Association for Computational Linguistics, 9074--9091. https://aclanthology.org/ 2022 .emnlp-main.618 Derek Chong, Jenny Hong, and Christopher D. Manning. 2022. Detecting Label Errors by Using Pre-Trained Language Models. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7--11, 2022, Yoav Goldberg, Zornitsa Kozareva, and Yue Zhang (Eds.). Association for Computational Linguistics, 9074--9091. https://aclanthology.org/2022.emnlp-main.618

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