Researchers can stop wasting 80% of their LLM classification budget

Researchers found a way to make large language models classify text for 80% less money. This means they can analyze far more data for the same budget, or save significant funds on existing projects.

Using large language models to classify text has been expensive, limiting how much data researchers could process. This paper shows that a simple change in how prompts are structured can drastically reduce those costs. It means researchers can now analyze much larger datasets, making studies more robust and comprehensive without needing bigger budgets.