An Active Learning Approach to Coreference Resolution

By Mrinmaya Sachan, Eduard H. Hovy, Eric P. Xing. 2015

23 citations recorded by the source corpus.

Subfields: Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Yang Trista Cao
2. Hal Daumé Iii
3. Yoav Goldberg
4. Daniel Klein
5. Mohit Bansal
6. Yejin Choi
7. Christopher D. Manning
8. Julia Kreutzer

Citations in the corpus

• Toward Gender-Inclusive Coreference Resolution (2019, methodology): “algorithms used are not statistically unbiased [Guha et al. 2015; Laws et al. 2012; Miller et al. 2012; Ng and Cardie 2003; Sachan et al. 2015].”
• Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle* (2021, methodology): “Considering the approaches used in dominant papers, the active learning algorithms used are not statistically unbiased (Ng and Cardie 2003; Laws, Heimerl, and Schütze 2012; Miller, Dligach, and Savova 2012; Sachan, Hovy, and Xing 2015; Guha et al. 2015).”