22 citations · 26 across the 3 of their papers we have counts for
5 papers
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…
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning
Chang Xu, Jun Wang, Yuqing Tang +3
As modern neural machine translation (NMT) systems have been widely deployed, their security vulnerabilities require close scrutiny. Most recently, NMT systems have been found vuln…
Deep Transformers with Latent Depth
Xian Li, Asa Cooper Stickland, Yuqing Tang +1
The Transformer model has achieved state-of-the-art performance in many sequence modeling tasks. However, how to leverage model capacity with large or variable depths is still an o…
Multilingual Speech Translation with Efficient Finetuning of Pretrained Models
Xian Li, Changhan Wang, Yun Tang +6
We present a simple yet effective approach to build multilingual speech-to-text (ST) translation by efficient transfer learning from pretrained speech encoder and text decoder. Our…