7 citations · 21 across the 6 of their papers we have counts for
15 papers
AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages
Machel Reid, Junjie Hu, Graham Neubig +1
Reproducible benchmarks are crucial in driving progress of machine translation research. However, existing machine translation benchmarks have been mostly limited to high-resource…
Phrase-level Active Learning for Neural Machine Translation
Junjie Hu, Graham Neubig
Neural machine translation (NMT) is sensitive to domain shift. In this paper, we address this problem in an active learning setting where we can spend a given budget on translating…
Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models
Po-Yao Huang, Mandela Patrick, Junjie Hu +3
This paper studies zero-shot cross-lingual transfer of vision-language models. Specifically, we focus on multilingual text-to-video search and propose a Transformer-based model tha…
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation
Sebastian Ruder, Noah Constant, Jan Botha +8
Machine learning has brought striking advances in multilingual natural language processing capabilities over the past year. For example, the latest techniques have improved the sta…
Explicit Alignment Objectives for Multilingual Bidirectional Encoders
Junjie Hu, Melvin Johnson, Orhan Firat +2
Pre-trained cross-lingual encoders such as mBERT (Devlin et al., 2019) and XLMR (Conneau et al., 2020) have proven to be impressively effective at enabling transfer-learning of NLP…
On Learning Language-Invariant Representations for Universal Machine Translation
Han Zhao, Junjie Hu, Andrej Risteski
The goal of universal machine translation is to learn to translate between any pair of languages, given a corpus of paired translated documents for \emph{a small subset} of all pai…