Self-Supervised Quality Estimation for Machine Translation

We propose a simple self-supervised method for quality estimation, which outperforms several previous unsupervised methods. (Read More)

TRICE: Gradual Finetuning for Multi-Source Sequence Generation

We propose TRICE, a task-agnostic Transferring fRamework for multI-sourCe sEquence generation. The transferring process is divided into two stages in the manner of gradual finetuning, which achieves state-of-the-art results on several challenging tasks. (Read More)

Mask-Align: Self-Supervised Neural Word Alignment

We propose Mask-Align, a self-supervised framework for neural word alignment, which outperforms several strong baselines by a large margin. (Read More)