Unsupervised Machine Translation

Kniha "Unsupervised Machine Translation" stručný popis:
For decades, machine translation between natural languages fundamentally relied on human-translated documents known as parallel texts, which provide direct correspondences between source and target sentences. The notion that translation systems could be trained on non-parallel texts, independently written in different languages, was long considered unrealistic. Fast forward to the era of large language models (LLMs), and we now know that given their sufficient computational resources, LLMs exploit incidental parallelism in their vast training data, i.e., they identify parallel messages across languages and learn to translate without explicit supervision. LLMs have since demonstrated the ability to perform translation tasks with impressive quality, rivaling systems specifically trained for translation. This monograph explores the fascinating journey that led to this point, focusing on...
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