LLMs for Now, Fine-Tuning for Later: An Ensemble Approach to Data Drift in Domain-Specific Tasks
Association for Computational Linguistics 2026, Hansu Gu, Toby Li, Tun Lu et autres
Deploying machine learning models in real-world domain-specific scenarios is challenged by the scarcity of expert annotations and by data drift, where the statistical properties of incoming data continuously evolve. Active Learning (AL) iteratively improves compact models with expert annotations but suffers from …
us, cn, mx (code pays fourni par la source)
0 citations
Underline Science Inc.