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1
EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification ...
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2
Delving Deeper into Cross-lingual Visual Question Answering ...
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3
Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ...
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4
IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages ...
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5
Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation ...
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6
Improving Word Translation via Two-Stage Contrastive Learning ...
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7
On cross-lingual retrieval with multilingual text encoders
Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer Science + Business Media, 2022
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8
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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9
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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10
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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11
SimLex-999 Slovenian translation SimLex-999-sl 1.0
Pollak, Senja; Vulić, Ivan; Pelicon, Andraž. - : University of Ljubljana, 2021
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12
Towards Zero-shot Language Modeling ...
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13
Multilingual and Cross-Lingual Intent Detection from Spoken Data ...
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14
Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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15
Modelling Latent Translations for Cross-Lingual Transfer ...
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16
Prix-LM: Pretraining for Multilingual Knowledge Base Construction ...
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17
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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18
xGQA: Cross-Lingual Visual Question Answering ...
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19
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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MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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