Systematic Comparison of Retrieval Techniques for Retrieval Augmented Neural Machine Translation

The choice of retrieval technique significantly impacts the performance of retrieval-augmented neural machine translation models, with varying effects across different architectures. Optimizing for coverage and diversity of retrieved examples can yield substantial gains, especially for non-autoregressive models.