David Anugraha

Online Language Adaptive Sampling for Better Distributed Cross-lingual Gains

This work proposes a simple yet effective adaptive sampling strategy that assigns trainable sampling probabilities to each language and employs an inner-outer optimization loop with a small overhead, leading to consistent performance improvements and, more importantly, distributing the gains across languages.