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1
Bi-directional Domain Adaptation Using Weighted MTL ...
Abstract: Domain adaption in syntactic parsing is still a significant challenge. We address the issue of data imbalance between the in-domain and out-of-domain treebank typically used for the problem. We define domain adaptation as a Multi-task learning (MTL) problem, which allows us to train two parsers, one for each domain. Our results show that the MTL approach is beneficial for the smaller treebank. For the larger treebank, we need to use loss weighting in order to avoid a decrease in performance below the single task. In order to determine to what degree the data imbalance between two domains and the domain differences affect results, we also carry out an experiment with two imbalanced in-domain treebanks and show that loss weighting also improves performance in an in-domain setting. Given loss weighting in MTL, we can improve results for both parsers. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/5jt1-hh42
https://underline.io/lecture/29935-bi-directional-domain-adaptation-using-weighted-mtl
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2
Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD ...
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3
What's in a Span? Evaluating the Creativity of a Span-Based Neural Constituency Parser
In: Proceedings of the Society for Computation in Linguistics (2021)
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4
Acoustic Analysis of high vowels in the Louisiana French of Terrebonne Parish
In: IULC Working Papers; Vol 16 No 1 (2016) ; 1524-2110 (2018)
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5
Brown clustering for unlexicalized parsing
Dakota, Daniel [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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6
From Discourse Representation Structure to Event Semantics: A Simple Conversion?
Dakota, Daniel [Verfasser]; Kübler, Sandra [Verfasser]; Ganzha, Maria [Herausgeber]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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7
IUCL at SemEval-2016 Task 6: An Ensemble Model for Stance Detection in Twitter
Liu, Can [Verfasser]; Li, Wen [Verfasser]; Demarest, Bradford [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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8
Parsing German: How Much Morphology Do We Need?
Maier, Wolfgang [Verfasser]; Kübler, Sandra [Verfasser]; Dakota, Daniel [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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9
“My Curiosity was Satisfied, but not in a Good Way”: Predicting User Ratings for Online Recipes
Liu, Can [Verfasser]; Guo, Chun [Verfasser]; Dakota, Daniel [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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10
Do FreeWord Order Languages Need More Treebank Data? Investigating Dative Alternation in German, English, and Russian
Gilmanov, Timur [Verfasser]; Abo Mokh, Noor [Verfasser]; Kim, Evgeny [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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11
Acoustic analysis of high vowels in the Louisiana French of Terrebonne Parish
Dakota, Daniel [Verfasser]; Kasper-Cushmann, Kelly [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
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12
“My Curiosity was Satisfied, but not in a Good Way”: Predicting User Ratings for Online Recipes [Online resource]
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13
Parsing German: How Much Morphology Do We Need? [Online resource]
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14
From Discourse Representation Structure to Event Semantics: A Simple Conversion? [Online resource]
IDS-Repository
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15
IUCL at SemEval-2016 Task 6: An Ensemble Model for Stance Detection in Twitter [Online resource]
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16
Do FreeWord Order Languages Need More Treebank Data? Investigating Dative Alternation in German, English, and Russian [Online resource]
IDS-Repository
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17
Brown clustering for unlexicalized parsing [Online resource]
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18
Acoustic analysis of high vowels in the Louisiana French of Terrebonne Parish [Online resource]
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