LexiLogic@CALCS 2025: Predicting Preferences in Generated Code-Switched Text

AbstractCode-switched generation is an emerging application in NLP systems, as code-switched text and speech are common and natural forms of conversation in multilingual communities worldwide. While monolingual generation has matured significantly with advances in large language models, code-switched generation still remains challenging, especially for languages and domains with less representation in pre-training datasets. In this paper, we describe our submission to the shared task of predicting human preferences for code-switched text in English-Malayalam, English-Tamil, and English-Hindi. We discuss our various approaches and report on the accuracy scores for each approach.