AI RESEARCH
Build, Borrow, or Just Fine-Tune? A Political Scientist's Guide to Choosing NLP Models
arXiv CS.CL
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ArXi:2603.09595v1 Announce Type: new Political scientists increasingly face a consequential choice when adopting natural language processing tools: build a domain-specific model from scratch, borrow and adapt an existing one, or simply fine-tune a general-purpose model on task data? Each approach occupies a different point on the spectrum of performance, cost, and required expertise, yet the discipline has offered little empirical guidance on how to navigate this trade-off. This paper provides such guidance.