97 citations · 198 across the 16 of their papers we have counts for
19 papers
A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU
Guanhua Chen, Yutong Yao, Derek F. Wong +1
Multi-intent natural language understanding (NLU) presents a formidable challenge due to the model confusion arising from multiple intents within a single utterance. While previous…
ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation
Zhaocong Li, Xuebo Liu, Derek F. Wong +2
Transfer learning is a simple and powerful method that can be used to boost model performance of low-resource neural machine translation (NMT). Existing transfer learning methods f…
RoBLEURT Submission for the WMT2021 Metrics Task
Yu Wan, Dayiheng Liu, Baosong Yang +6
In this paper, we present our submission to Shared Metrics Task: RoBLEURT (Robustly Optimizing the training of BLEURT). After investigating the recent advances of trainable metrics…
Variance-Aware Machine Translation Test Sets
Runzhe Zhan, Xuebo Liu, Derek F. Wong +1
We release 70 small and discriminative test sets for machine translation (MT) evaluation called variance-aware test sets (VAT), covering 35 translation directions from WMT16 to WMT…
On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation
Xuebo Liu, Longyue Wang, Derek F. Wong +4
Pre-training (PT) and back-translation (BT) are two simple and powerful methods to utilize monolingual data for improving the model performance of neural machine translation (NMT).…
Difficulty-Aware Machine Translation Evaluation
Runzhe Zhan, Xuebo Liu, Derek F. Wong +1
The high-quality translation results produced by machine translation (MT) systems still pose a huge challenge for automatic evaluation. Current MT evaluation pays the same attentio…