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Hits 81 – 100 of 2.974

81
Data for: Psycholinguistic dataset on language use in 1145 novels published in English and Dutch ...
Van Cranenburgh, Andreas. - : Mendeley, 2021
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82
Graph-to-Graph Translations To Augment Abstract Meaning Representation Tense And Aspect ...
Bakal, Mollie. - : My University, 2021
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83
A Journey in Linguistic Computing from Father Busa to Linguistic Linked Data ...
Passarotti, Marco. - : Zenodo, 2021
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84
A Journey in Linguistic Computing from Father Busa to Linguistic Linked Data ...
Passarotti, Marco. - : Zenodo, 2021
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85
Signed Coreference Resolution ...
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86
Including Signed Languages in Natural Language Processing ...
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87
Key to BibleWorks Greek Morphology (BGM) ...
Bilby, Mark Glen. - : Zenodo, 2021
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88
Key to BibleWorks Greek Morphology (BGM) ...
Bilby, Mark Glen. - : Zenodo, 2021
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89
Backtranslation in Neural Morphological Inflection ...
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90
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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91
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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92
The Reading Machine: a Versatile Framework for Studying Incremental Parsing Strategies ...
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93
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
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94
Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
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95
A Prototype Free/Open-Source Morphological Analyser and Generator for Sakha ...
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96
Automatic Error Type Annotation for Arabic ...
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97
Developing Conversational Data and Detection of Conversational Humor in Telugu ...
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98
Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.279 Abstract: How does the input segmentation of pretrained language models (PLMs) affect their interpretations of complex words? We present the first study investigating this question, taking BERT as the example PLM and focusing on its semantic representations of English derivatives. We show that PLMs can be interpreted as serial dual-route models, i.e., the meanings of complex words are either stored or else need to be computed from the subwords, which implies that maximally meaningful input tokens should allow for the best generalization on new words. This hypothesis is confirmed by a series of semantic probing tasks on which DelBERT (Derivation leveraging BERT), a model with derivational input segmentation, substantially outperforms BERT with WordPiece segmentation. Our results suggest that the generalization capabilities of PLMs could be further improved if a morphologically-informed vocabulary of input tokens were used. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Morphology; Neural Network; Semantics
URL: https://underline.io/lecture/25622-superbizarre-is-not-superb-derivational-morphology-improves-bert's-interpretation-of-complex-words
https://dx.doi.org/10.48448/0kb6-8w78
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99
HIT - A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation ...
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100
Minimally-Supervised Morphological Segmentation using Adaptor Grammars with Linguistic Priors ...
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