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Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation
Akiko Eriguchi, Melvin Johnson, Orhan Firat +2
Transferring representations from large supervised tasks to downstream tasks has shown promising results in AI fields such as Computer Vision and Natural Language Processing (NLP).…
Training Deeper Neural Machine Translation Models with Transparent Attention
Ankur Bapna, Mia Xu Chen, Orhan Firat +2
While current state-of-the-art NMT models, such as RNN seq2seq and Transformers, possess a large number of parameters, they are still shallow in comparison to convolutional models…
Revisiting Character-Based Neural Machine Translation with Capacity and Compression
Colin Cherry, George Foster, Ankur Bapna +2
Translating characters instead of words or word-fragments has the potential to simplify the processing pipeline for neural machine translation (NMT), and improve results by elimina…
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation
Mia Xu Chen, Orhan Firat, Ankur Bapna +9
The past year has witnessed rapid advances in sequence-to-sequence (seq2seq) modeling for Machine Translation (MT). The classic RNN-based approaches to MT were first out-performed…