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Machine translation is the automated process of converting text or speech from one language into another using computer software. It employs various computational techniques, from rule-based to neural networks, to facilitate cross-lingual communication.
Dolma is a multilingual dataset designed for natural language processing research, focusing on low-resource languages. It provides parallel corpora and annotated data to support machine translation and cross-lingual understanding.
Lookahead decoding is a computational strategy used in natural language processing and speech recognition that involves anticipating future inputs or outputs to improve decision-making during sequence generation. By considering possible future tokens or states before finalizing a current choice, lookahead decoding aims to enhance accuracy and performance in tasks involving sequential data.