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arXiv · 2506.07583

Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models

Ramakrishna Appicharla·Baban Gain·Santanu Pal·Asif Ekbal
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Abstract

Despite the popularity of the large language models (LLMs), their application to machine translation is relatively underexplored, especially in context-aware settings. This work presents a literature review of context-aware translation with LLMs. The existing works utilise prompting and fine-tuning approaches, with few focusing on automatic post-editing and creating translation agents for context-aware machine translation. We observed that the commercial LLMs (such as ChatGPT and Tower LLM) achieved better results than the open-source LLMs (such as Llama and Bloom LLMs), and prompt-based approaches serve as good baselines to assess the quality of translations. Finally, we present some interesting future directions to explore.

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Ramakrishna Appicharla, Baban Gain, Santanu Pal, Asif Ekbal. 2025-06-09. Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models. https://arxiv.org/abs/2506.07583

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