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The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021 (2)
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Hits 1 – 7 of 7
1
"We will Reduce Taxes" - Identifying Election Pledges with Language Models ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Adhikari, pankaj.adhikari@monash.edu
;
Fornaciari, Tommaso
. - : Underline Science Inc., 2021
BASE
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2
SemEval 2021 Task 12: Learning with Disagreement ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Chamberlain, Jon
;
Dumitrache, Anca
;
Fornaciari, Tommaso
;
Miller, Tristan
;
Plank, Barbara
;
Poesio, Massimo
;
Simpson, Edwin
;
Uma, Alexandra
. - : Underline Science Inc., 2021
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
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Electromagnetism
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FOS Physical sciences
;
Information and Knowledge Engineering
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;
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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3
SemEval-2021 Task 12: Learning with Disagreements
Uma, Alexandra
;
Fornaciari, Tommaso
;
Dumitrache, Anca
. - : Association for Computational Linguistics, 2021
BASE
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4
We Need to Consider Disagreement in Evaluation
Basile, Valerio
;
Fell, Michael
;
Fornaciari, Tommaso
. - : Association for Computational Linguistics, 2021. : country:USA, 2021. : place:Stroudsburg, PA, 2021
BASE
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5
Fake opinion detection: how similar are crowdsourced datasets to real data? [<Journal>]
Fornaciari, Tommaso
[Verfasser];
Cagnina, Leticia
[Verfasser];
Rosso, Paolo
[Verfasser].
DNB Subject Category Language
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6
Fake Opinion Detection: How Similar are Crowdsourced Datasets to Real Data?
Fornaciari, Tommaso
;
Cagnina, Leticia
;
Rosso, Paolo
. - : Springer-Verlag, 2020
BASE
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7
Identifying fake Amazon reviews as learning from crowds
Fornaciari, Tommaso
;
Poesio, Massimo
. - : Association for Computational Linguistics, 2014
BASE
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