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Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation ...
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BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling ...
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Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ...
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Learning Fast Adaptation on Cross-Accented Speech Recognition ...
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Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual Learning ...
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Meta-Transfer Learning for Code-Switched Speech Recognition ...
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On the Importance of Word Order Information in Cross-lingual Sequence Labeling ...
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Abstract:
Word order variances generally exist in different languages. In this paper, we hypothesize that cross-lingual models that fit into the word order of the source language might fail to handle target languages. To verify this hypothesis, we investigate whether making models insensitive to the word order of the source language can improve the adaptation performance in target languages. To do so, we reduce the source language word order information fitted to sequence encoders and observe the performance changes. In addition, based on this hypothesis, we propose a new method for fine-tuning multilingual BERT in downstream cross-lingual sequence labeling tasks. Experimental results on dialogue natural language understanding, part-of-speech tagging, and named entity recognition tasks show that reducing word order information fitted to the model can achieve better zero-shot cross-lingual performance. Furthermore, our proposed methods can also be applied to strong cross-lingual baselines, and improve their ... : Accepted in AAAI-2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2001.11164 https://dx.doi.org/10.48550/arxiv.2001.11164
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Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems ...
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Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables ...
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Towards Universal End-to-End Affect Recognition from Multilingual Speech by ConvNets ...
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Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentences ...
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Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition ...
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GlobalTrait: Personality Alignment of Multilingual Word Embeddings ...
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Learn to Code-Switch: Data Augmentation using Copy Mechanism on Language Modeling ...
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Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems ...
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Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition ...
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Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning ...
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