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• W3120896619 abstract "The paper presents the submission by HW-TSC in the WMT 2020 Automatic Post Editing Shared Task. We participate in the English-German and English-Chinese language pairs. Our system is built based on the Transformer pre-trained on WMT 2019 and WMT 2020 News Translation corpora, and fine-tuned on the APE corpus. Bottleneck Adapter Layers are integrated into the model to prevent over-fitting. We further collect external translations as the augmented MT candidates to improve the performance. The experiment demonstrates that pre-trained NMT models are effective when fine-tuning with the APE corpus of a limited size, and the performance can be further improved with external MT augmentation. Our system achieves competitive results on both directions in the final evaluation." @default.
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• W3120896619 date "2020-11-01" @default.
• W3120896619 modified "2023-09-23" @default.
• W3120896619 title "HW-TSC’s Participation at WMT 2020 Automatic Post Editing Shared Task" @default.
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