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Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations ...
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MFAQ: a Multilingual FAQ Dataset ...
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Mapping probability word problems to executable representations ...
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4
Interlocutors’ Age Impacts Teenagers’ Online Writing Style: Accommodation in Intra- and Intergenerational Online Conversations
In: Front Artif Intell (2021)
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Current limitations in cyberbullying detection: On evaluation criteria, reproducibility, and data scarcity [<Journal>]
Emmery, Chris [Verfasser]; Verhoeven, Ben [Verfasser]; Pauw, Guy De [Verfasser].
DNB Subject Category Language
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6
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
In: Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-02892154 ; Language Resources and Evaluation Conference, ELDA/ELRA, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/en/ (2020)
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The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene
Daelemans, Walter; Fišer, Darja; Franza, Jasmin. - : Jožef Stefan Institute, 2020. : Centre for Computational Linguistics and Psycholinguistics (CLiPS), 2020
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The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
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The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
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10
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
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11
Neural Machine Translation of Artwork Titles Using Iconclass Codes ...
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12
A deep generative approach to native language identification ...
Abstract: Native language identification (NLI) – identifying the native language (L1) of a person based on his/her writing in the second language (L2) – is useful for a variety of purposes, including mar- keting, security, and educational applications. From a traditional machine learning perspective, NLI is usually framed as a multi-class classification task, where numerous designed features are combined in order to achieve state-of-the-art results. We introduce a deep generative language modelling (LM) approach to NLI, which consists in fine-tuning a GPT-2 model separately on texts written by the authors with the same L1, and assigning a label to an unseen text based on the minimum LM loss with respect to one of these fine-tuned GPT-2 models. Our method out- performs traditional machine learning approaches and currently achieves the best results on the benchmark NLI datasets. ...
Keyword: Computer and Information Science; Natural Language Processing; Neural Network
URL: https://underline.io/lecture/6242-a-deep-generative-approach-to-native-language-identification
https://dx.doi.org/10.48448/kkcb-j791
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13
Effective weakly supervised semantic frame induction using expression sharing in hierarchical hidden Markov models ...
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14
What makes a distributional context useful? Lexical diversity is more important than frequency ...
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15
Children Probably Store Short Rather Than Frequent or Predictable Chunks: Quantitative Evidence From a Corpus Study
Grimm, Robert; Cassani, Giovanni; Gillis, Steven. - : Frontiers Media S.A., 2019
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16
Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-domain Authorship Attribution and Style Change Detection
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17
Multilingual Cross-domain Perspectives on Online Hate Speech ...
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18
Patient representation learning and interpretable evaluation using clinical notes ...
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19
Lexical category acquisition is facilitated by uncertainty in distributional co-occurrences
Cassani, Giovanni; Grimm, Robert; Daelemans, Walter. - : Public Library of Science, 2018
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20
Leveraging Lexical-Semantic Knowledge for Text Classification Tasks
Gurevych, Iryna Akademischer Betreuer]. - Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2017
DNB Subject Category Language
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