Shuyun Yang

Tuning Less, Prompting More: In-Context Preference Learning Pipeline for Natural Language Transformation

Natural language transformation (NLT) tasks, such as machine translation (MT) and text style transfer (TST), require models to generate accurate and contextually appropriate outputs. However, existing approaches face significant challenges, including the computational costs of leveraging large pre-t