Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future

5 June 2022

Papers citing "Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future"

9 / 9 papers shown

Title
Validating LLM-as-a-Judge Systems in the Absence of Gold Labels Luke M. Guerdan Solon Barocas Kenneth Holstein Hanna M. Wallach Zhiwei Steven Wu Alexandra Chouldechova ALM ELM 147 0 0 13 Mar 2025
CoverBench: A Challenging Benchmark for Complex Claim Verification Alon Jacovi Moran Ambar Eyal Ben-David Uri Shaham Amir Feder Mor Geva Dror Marcus Avi Caciularu LMTD 45 3 0 06 Aug 2024
DCA-Bench: A Benchmark for Dataset Curation Agents Benhao Huang Yingzhuo Yu Jin Huang Xingjian Zhang Jiaqi Ma 28 1 0 11 Jun 2024
What's the Meaning of Superhuman Performance in Today's NLU? Simone Tedeschi Johan Bos T. Declerck Jan Hajic Daniel Hershcovich ... Simon Krek Steven Schockaert Rico Sennrich Ekaterina Shutova Roberto Navigli ELM LM&MA VLM ReLM LRM 24 26 0 15 May 2023
The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation Barbara Plank 22 96 0 04 Nov 2022
Stop Measuring Calibration When Humans Disagree Joris Baan Wilker Aziz Barbara Plank Raquel Fernández 16 53 0 28 Oct 2022
Detecting Label Errors in Token Classification Data Wei-Chen Wang Jonas W. Mueller 19 13 0 08 Oct 2022
Efficient Methods for Natural Language Processing: A Survey Marcos Vinícius Treviso Ji-Ung Lee Tianchu Ji Betty van Aken Qingqing Cao ... Emma Strubell Niranjan Balasubramanian Leon Derczynski Iryna Gurevych Roy Schwartz 28 109 0 31 Aug 2022
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015