Large-Language-Model-Enhanced Adaptive Optimization for Data-Limited Multi-Domain Machine Translation
DKA-LLM-MT is proposed, a large-language-model-enhanced adaptive optimization framework for data-limited multi-domain machine translation that provides an effective and reliable solution for domain-sensitive machine translation under limited bilingual supervision and offers practical support for bilingual reading, specialized translation assistance, and domain-oriented language learning.