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1
Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation ...
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2
Language Models are Few-shot Multilingual Learners ...
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3
BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling ...
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4
Are Multilingual Models Effective in Code-Switching? ...
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5
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ...
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6
Learning Fast Adaptation on Cross-Accented Speech Recognition ...
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7
Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual Learning ...
Abstract: Recently, fine-tuning pre-trained language models (e.g., multilingual BERT) to downstream cross-lingual tasks has shown promising results. However, the fine-tuning process inevitably changes the parameters of the pre-trained model and weakens its cross-lingual ability, which leads to sub-optimal performance. To alleviate this problem, we leverage continual learning to preserve the original cross-lingual ability of the pre-trained model when we fine-tune it to downstream tasks. The experimental result shows that our fine-tuning methods can better preserve the cross-lingual ability of the pre-trained model in a sentence retrieval task. Our methods also achieve better performance than other fine-tuning baselines on the zero-shot cross-lingual part-of-speech tagging and named entity recognition tasks. ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://arxiv.org/abs/2004.14218
https://dx.doi.org/10.48550/arxiv.2004.14218
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8
XPersona: Evaluating Multilingual Personalized Chatbot ...
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9
Meta-Transfer Learning for Code-Switched Speech Recognition ...
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10
On the Importance of Word Order Information in Cross-lingual Sequence Labeling ...
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11
Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems ...
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12
Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables ...
Liu, Zihan; Shin, Jamin; Xu, Yan. - : arXiv, 2019
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13
Towards Universal End-to-End Affect Recognition from Multilingual Speech by ConvNets ...
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14
Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentences ...
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15
Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition ...
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16
GlobalTrait: Personality Alignment of Multilingual Word Embeddings ...
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17
Learn to Code-Switch: Data Augmentation using Copy Mechanism on Language Modeling ...
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18
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems ...
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19
Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition ...
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20
Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning ...
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