373 citations · 842 across the 24 of their papers we have counts for
8 papers · 1 filter
Alternative Input Signals Ease Transfer in Multilingual Machine Translation
Simeng Sun, Angela Fan, James Cross +4
Recent work in multilingual machine translation (MMT) has focused on the potential of positive transfer between languages, particularly cases where higher-resourced languages can b…
Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications
Shuo Sun, Ahmed El-Kishky, Vishrav Chaudhary +3
Sentence-level Quality estimation (QE) of machine translation is traditionally formulated as a regression task, and the performance of QE models is typically measured by Pearson co…
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation
Jun Wang, Chang Xu, Francisco Guzman +3
Mistranslated numbers have the potential to cause serious effects, such as financial loss or medical misinformation. In this work we develop comprehensive assessments of the robust…
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning
Jun Wang, Chang Xu, Francisco Guzman +4
Neural machine translation systems are known to be vulnerable to adversarial test inputs, however, as we show in this paper, these systems are also vulnerable to training attacks.…
LAWDR: Language-Agnostic Weighted Document Representations from Pre-trained Models
Hongyu Gong, Vishrav Chaudhary, Yuqing Tang +1
Cross-lingual document representations enable language understanding in multilingual contexts and allow transfer learning from high-resource to low-resource languages at the docume…
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation
Naman Goyal, Cynthia Gao, Vishrav Chaudhary +7
One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the lack of good evaluation benchmarks. Current evaluation benchmarks eithe…
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data
Wei-Jen Ko, Ahmed El-Kishky, Adithya Renduchintala +6
The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are lin…
Quality Estimation without Human-labeled Data
Yi-Lin Tuan, Ahmed El-Kishky, Adithya Renduchintala +3
Quality estimation aims to measure the quality of translated content without access to a reference translation. This is crucial for machine translation systems in real-world scenar…