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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 (4)
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Hits 1 – 4 of 4
1
{PROST}: {P}hysical Reasoning about Objects through Space and Time ...
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
;
Aroca-Ouellette, Stéphane
;
Kann, Katharina
. - : Underline Science Inc., 2021
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2
Don't Rule Out Monolingual Speakers: A Method For Crowdsourcing Machine Translation Data ...
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
;
Bhatnagar, Rajat
;
Ganesh, Ananya
. - : Underline Science Inc., 2021
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3
What Would a Teacher Do? {P}redicting Future Talk Moves ...
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
;
Ganesh, Ananya
;
Kann, Katharina
;
Palmer, Martha
. - : Underline Science Inc., 2021
Abstract:
Read paper: https://www.aclanthology.org/2021.findings-acl.418 Abstract: Recent advances in natural language processing (NLP) have the ability to transform how classroom learning takes place. Combined with the increasing integration of technology in today's classrooms, NLP systems leveraging question answering and dialog processing techniques can serve as private tutors or participants in classroom discussions to increase student engagement and learning. To progress towards this goal, we use the classroom discourse framework of academically productive talk (APT) to learn strategies that make for the best learning experience. In this paper, we introduce a new task, called future talk move prediction (FTMP): it consists of predicting the next talk move -- an utterance strategy from APT -- given a conversation history with its corresponding talk moves. We further introduce a neural network model for this task, which outperforms multiple baselines by a large margin. Finally, we compare our model's performance on ...
Keyword:
Computational Linguistics
;
Condensed Matter Physics
;
Deep Learning
;
Electromagnetism
;
FOS Physical sciences
;
Neural Network
;
Semantics
URL:
https://underline.io/lecture/26509-what-would-a-teacher-doquestion-predicting-future-talk-moves
https://dx.doi.org/10.48448/5nye-xk44
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4
How to Adapt Your Pretrained Multilingual Model to 1600 Languages ...
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
;
Ebrahimi, Abteen
;
Kann, Katharina
. - : Underline Science Inc., 2021
BASE
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