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LLMs move beyond sentence-level translation with new RAG system

Researchers have developed a new system called PAT (Pragmatic Auto-Translator) that aims to move Large Language Models (LLMs) beyond sentence-by-sentence translation. PAT utilizes retrieval-augmented generation (RAG) to incorporate context from comparable corpora of authentic texts, enabling whole-document translation. The system was evaluated on translations from U.S. English into Latin American and Mexican Spanish, showing that while LLMs can be guided towards reformulation beyond the sentence level, further work is needed to enhance the effectiveness of these reformulations. AI

IMPACT This research explores new methods for LLMs to perform whole-document translation, potentially improving the quality and context-awareness of machine translation systems.

RANK_REASON Research paper detailing a new method for LLM translation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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LLMs move beyond sentence-level translation with new RAG system

COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Alaina Brandt ·

    Can an Old Dog Be Taught New Tricks? Taking LLMs Beyond Sentence Level Translation

    Automatic translation systems, from CAT tools to MT, overwhelmingly treat translation as a sentence-by-sentence act. This paper asks whether LLMs can be moved beyond that paradigm through whole-document, corpus-informed translation. We present PAT (Pragmatic Auto-Translator), a R…