3 papers
cs.CL2025
Adapting Multilingual Models to Code-Mixed Tasks via Model Merging
Prashant Kodali, Vaishnavi Shivkumar, Swarang Joshi +3
We study model merging as a practical alternative to conventional adaptation strategies for code-mixed NLP. Starting from a multilingual base model, we: (i) perform continued pre-t…
cs.CL2024
Benchmarks Underestimate the Readiness of Multi-lingual Dialogue Agents
Andrew H. Lee, Sina J. Semnani, Galo Castillo-López +16
Creating multilingual task-oriented dialogue (TOD) agents is challenging due to the high cost of training data acquisition. Following the research trend of improving training data…
cs.CL2024
From Human Judgements to Predictive Models: Unravelling Acceptability in Code-Mixed Sentences
Prashant Kodali, Anmol Goel, Likhith Asapu +5
Current computational approaches for analysing or generating code-mixed sentences do not explicitly model ``naturalness'' or ``acceptability'' of code-mixed sentences, but rely on…