Toward Annotator Group Bias in Crowdsourcing
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)2022pp. 1797–1806
Citations Over TimeTop 17% of 2022 papers
Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Seung Yang, Youlong Cheng, Hui Liu, Jiliang Tang
Abstract
Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu, Jiliang Tang. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.
Related Papers
- → Automatic annotation of image databases based on implicit crowdsourcing, visual concept modeling and evolution(2012)23 cited
- → Annotating Relations Between Named Entities with Crowdsourcing(2018)8 cited
- → A Classification Model for Diverse and Noisy Labelers(2017)2 cited
- Susquehanna Chorale Spring Concert "Roots and Wings"(2017)
- → DETERMINING QUALITY REQUIREMENTS AT THE UNIVERSITIES TO IMPROVE THE QUALITY OF EDUCATION(2018)