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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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2
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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3
Verb Knowledge Injection for Multilingual Event Processing ...
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4
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
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5
Verb Knowledge Injection for Multilingual Event Processing ...
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6
Probing Pretrained Language Models for Lexical Semantics ...
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7
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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8
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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9
Specializing unsupervised pretraining models for word-level semantic similarity
Ponti, Edoardo Maria; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, ACL, 2020
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10
Classification-based self-learning for weakly supervised bilingual lexicon induction
Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020
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11
Probing pretrained language models for lexical semantics
Vulić, Ivan; Korhonen, Anna; Litschko, Robert. - : Association for Computational Linguistics, 2020
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12
XCOPA: A multilingual dataset for causal commonsense reasoning
Ponti, Edoardo Maria; Majewska, Olga; Liu, Qianchu. - : Association for Computational Linguistics, 2020
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13
Improving bilingual lexicon induction with unsupervised post-processing of monolingual word vector spaces
Glavaš, Goran; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, 2020
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14
SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment
Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020
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15
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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16
Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ...
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17
Multilingual and cross-lingual graded lexical entailment
Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019
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18
How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions
Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019
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19
Cross-lingual semantic specialization via lexical relation induction
Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019
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20
Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment
Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019
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