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SemEval 2021 Task 12: Learning with Disagreement ...
Abstract: Disagreement between coders is ubiquitous in virtually all datasets annotated with human judgements in both natural language processing and computer vision. However, most supervised machine learning methods assumethat a single preferred interpretation exists for each item, which is at best an idealization. The aim of the SemEval-2021 shared task on Learning with Disagreements (Le-wi-Di) wasto provide a unified testing framework for methods for learning from data containing multiple and possibly contradictory annotations covering the best-known datasets containing information about disagreements for interpreting language and classifying images. In this paper we describe the shared task and its results. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/30027-semeval-2021-task-12-learning-with-disagreement
https://dx.doi.org/10.48448/jnrq-9d84
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SemEval-2021 Task 12: Learning with Disagreements
Uma, Alexandra; Fornaciari, Tommaso; Dumitrache, Anca. - : Association for Computational Linguistics, 2021
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Capturing Ambiguity in Crowdsourcing Frame Disambiguation ...
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Capturing Ambiguity in Crowdsourcing Frame Disambiguation
In: Proceedings of the AAAI Conference on Human Computation and Crowdsourcing; Vol. 6 No. 1 (2018): Sixth AAAI Conference on Human Computation and Crowdsourcing (2018)
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