13 citations · 18 across the 2 of their papers we have counts for
9 papers
Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning
Daniel Edmiston, Phillip Keung, Noah A. Smith
Cross-lingual transfer learning without labeled target language data or parallel text has been surprisingly effective in zero-shot cross-lingual classification, question answering,…
Unsupervised Bitext Mining and Translation via Self-trained Contextual Embeddings
Phillip Keung, Julian Salazar, Yichao Lu +1
We describe an unsupervised method to create pseudo-parallel corpora for machine translation (MT) from unaligned text. We use multilingual BERT to create source and target sentence…
The Multilingual Amazon Reviews Corpus
Phillip Keung, Yichao Lu, György Szarvas +1
We present the Multilingual Amazon Reviews Corpus (MARC), a large-scale collection of Amazon reviews for multilingual text classification. The corpus contains reviews in English, J…
Improving Non-autoregressive Neural Machine Translation with Monolingual Data
Jiawei Zhou, Phillip Keung
Non-autoregressive (NAR) neural machine translation is usually done via knowledge distillation from an autoregressive (AR) model. Under this framework, we leverage large monolingua…
Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings
Phillip Keung, Yichao Lu, Julian Salazar +1
Multilingual contextual embeddings have demonstrated state-of-the-art performance in zero-shot cross-lingual transfer learning, where multilingual BERT is fine-tuned on one source…
Attentional Speech Recognition Models Misbehave on Out-of-domain Utterances
Phillip Keung, Wei Niu, Yichao Lu +2
We discuss the problem of echographic transcription in autoregressive sequence-to-sequence attentional architectures for automatic speech recognition, where a model produces very l…