While machine translation has improved dramatically for major languages, quality translation still lags for thousands of smaller languages.

Machine translation has improved immensely thanks to AI, but handling multiple languages remains tricky. Researchers from Tel Aviv University and Meta studied this challenge. Through systematic experiments, they uncovered what really causes the most interference.

Researchers at Carnegie Mellon University and University of Lisbon systematically studied when context is needed for high-quality translation across 14 languages.