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1
Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations ...
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MFAQ: a Multilingual FAQ Dataset ...
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3
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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7
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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9
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 ...
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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
Abstract: One of the tasks faced by young children is the segmentation of a continuous stream of speech into discrete linguistic units. Early in development, syllables emerge as perceptual primitives, and the wholesale storage of syllable chunks is one possible strategy for bootstrapping the segmentation process. Here, we investigate what types of chunks children store. Our method involves selecting syllabified utterances from corpora of child-directed speech, which we vary according to (a) their length in syllables, (b) the mutual predictability of their syllables, and (c) their frequency. We then use the number of utterances within which words are contained to predict the time course of word learning, arguing that utterances which perform well at this task are also more likely to be stored, by young children, as undersegmented chunks. Our results show that short utterances are best-suited for predicting when children acquire the words contained within them, although the effect is rather small. Beyond this, we also find that short utterances are the most likely to correspond to words. Together, the two findings suggest that children may not store many complete utterances as undersegmented chunks, with most of the units that children store as hypothesized words corresponding to actual words. However, dovetailing with an item-based account of language-acquisition, when children do store undersegmented chunks, these are likely to be short sequences—not frequent or internally predictable multi-word chunks. We end by discussing implications for work on formulaic multi-word sequences.
Keyword: Psychology
URL: https://doi.org/10.3389/fpsyg.2019.00080
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6363945/
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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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