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

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.

@article{appicharla2025_2506.07583,
  title={ Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models },
  author={ Ramakrishna Appicharla and Baban Gain and Santanu Pal and Asif Ekbal },
  journal={arXiv preprint arXiv:2506.07583},
  year={ 2025 }
}