Highlights from Machine Translation and Multilinguality in March 2023
Here is what I found the most interesting in MT and multilinguality in March
- I only feature two papers (both from Microsoft, co-incidence), not
because there were too few on arXiv, but because I did not manage to read that
much this month.
In this paper, folks from Microsoft in India experiment with zero-shot
crosslingual transfer for classification. They use a multi-task learning setup.
Besides performing the task in the source language, they teach the model using
a two-player game. There is a discriminator (or adversarial classifier) that
tries to detect what language the sentence is in. The model itself then tries
to fool the discriminator and conceal the language identity. They get good
results on cross-lingual natural language inference, including the difficult
AmericasNLI data that contain indigenous languages of