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1
EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification ...
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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 ...
Abstract: Can we construct a neural model that is inductively biased towards learning human languages? Motivated by this question, we aim at constructing an informative prior over neural weights, in order to adapt quickly to held-out languages in the task of character-level language modeling. We infer this distribution from a sample of typologically diverse training languages via Laplace approximation. The use of such a prior outperforms baseline models with an uninformative prior (so-called "fine-tuning") in both zero-shot and few-shot settings. This shows that the prior is imbued with universal phonological knowledge. Moreover, we harness additional language-specific side information as distant supervision for held-out languages. Specifically, we condition language models on features from typological databases, by concatenating them to hidden states or generating weights with hyper-networks. These features appear beneficial in the few-shot setting, but not in the zero-shot setting. Since the paucity of digital texts ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2108.03334
https://dx.doi.org/10.48550/arxiv.2108.03334
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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 ...
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20
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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