Acronym Disambiguation

Acronym disambiguation focuses on automatically identifying and resolving the meaning of ambiguous acronyms within text, a crucial task for natural language processing across various domains. Current research emphasizes improving the accuracy of acronym disambiguation using transformer-based language models like BERT, often enhanced through techniques such as prompt engineering, contrastive learning, and parameter-efficient fine-tuning to adapt to specific domains or languages. This work is significant because accurate acronym resolution is essential for improving the efficiency and effectiveness of information retrieval, machine translation, and other NLP applications, particularly in specialized fields like medicine and science where acronyms are prevalent.