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Hits 1 – 2 of 2
1
Improving Cross-Lingual Reading Comprehension with Self-Training ...
Huang, Wei-Cheng
;
Huang, Chien-yu
;
Lee, Hung-yi
. - : arXiv, 2021
Abstract:
Substantial improvements have been made in machine reading comprehension, where the machine answers questions based on a given context. Current state-of-the-art models even surpass human performance on several benchmarks. However, their abilities in the cross-lingual scenario are still to be explored. Previous works have revealed the abilities of pre-trained multilingual models for zero-shot cross-lingual reading comprehension. In this paper, we further utilized unlabeled data to improve the performance. The model is first supervised-trained on source language corpus, and then self-trained with unlabeled target language data. The experiment results showed improvements for all languages, and we also analyzed how self-training benefits cross-lingual reading comprehension in qualitative aspects. ... : 8 pages, 4 figures ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://arxiv.org/abs/2105.03627
https://dx.doi.org/10.48550/arxiv.2105.03627
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2
Defending Your Voice: Adversarial Attack on Voice Conversion ...
Huang, Chien-yu
;
Lin, Yist Y.
;
Lee, Hung-yi
. - : arXiv, 2020
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