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1
XHate-999: analyzing and detecting abusive language across domains and languages
Glavaš, Goran [Verfasser]; Karan, Mladen [Verfasser]; Vulic, Ivan [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021
DNB Subject Category Language
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2
Specializing unsupervised pretraining models for word-level semantic similarity
Lauscher, Anne [Verfasser]; Vulic, Ivan [Verfasser]; Ponti, Edoardo Maria [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021
DNB Subject Category Language
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3
Towards instance-level parser selection for cross-lingual transfer of dependency parsers
Litschko, Robert [Verfasser]; Vulic, Ivan [Verfasser]; Agić, Želiko [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021
DNB Subject Category Language
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4
Data for paper: "Evaluating Resource-Lean Cross-Lingual Embedding Models in Unsupervised Retrieval" ...
Litschko, Robert; Glavaš, Goran. - : Mannheim University Library, 2021
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5
Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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6
On Cross-Lingual Retrieval with Multilingual Text Encoders ...
Abstract: In this work we present a systematic empirical study focused on the suitability of the state-of-the-art multilingual encoders for cross-lingual document and sentence retrieval tasks across a number of diverse language pairs. We first treat these models as multilingual text encoders and benchmark their performance in unsupervised ad-hoc sentence- and document-level CLIR. In contrast to supervised language understanding, our results indicate that for unsupervised document-level CLIR -- a setup with no relevance judgments for IR-specific fine-tuning -- pretrained multilingual encoders on average fail to significantly outperform earlier models based on CLWEs. For sentence-level retrieval, we do obtain state-of-the-art performance: the peak scores, however, are met by multilingual encoders that have been further specialized, in a supervised fashion, for sentence understanding tasks, rather than using their vanilla 'off-the-shelf' variants. Following these results, we introduce localized relevance matching for ... : to appear in IRJ ECIR 2021 Special Issue. arXiv admin note: substantial text overlap with arXiv:2101.08370 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; H.3.3; I.2.7; Information Retrieval cs.IR
URL: https://dx.doi.org/10.48550/arxiv.2112.11031
https://arxiv.org/abs/2112.11031
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7
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
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8
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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9
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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10
Verb Knowledge Injection for Multilingual Event Processing ...
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11
Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation
Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2021
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12
Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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13
Training and domain adaptation for supervised text segmentation
Glavaš, Goran; Ganesh, Ananya; Somasundaran, Swapna. - : Association for Computational Linguistics, 2021
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