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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 ...
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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 ...
Abstract: In task-oriented dialogue (ToD), a user holds a conversation with an artificial agent to complete a concrete task. Although this technology represents one of the central objectives of AI and has been the focus of ever more intense research and development efforts, it is currently limited to a few narrow domains (e.g., food ordering, ticket booking) and a handful of languages (e.g., English, Chinese). This work provides an extensive overview of existing methods and resources in multilingual ToD as an entry point to this exciting and emerging field. We find that the most critical factor preventing the creation of truly multilingual ToD systems is the lack of datasets in most languages for both training and evaluation. In fact, acquiring annotations or human feedback for each component of modular systems or for data-hungry end-to-end systems is expensive and tedious. Hence, state-of-the-art approaches to multilingual ToD mostly rely on (zero- or few-shot) cross-lingual transfer from resource-rich languages ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2104.08570
https://dx.doi.org/10.48550/arxiv.2104.08570
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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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