Evaluating Answer Quality and LLM-Based Assessment in a Zero-Marginal-Cost Retrieval-Augmented Generation Agricultural Advisory System
Agricultural decision-making often depends on timely, evidence-based advice, yet advisory systems for underserved farming communities must also be cost-effective enough to operate continuously. Retrieval-augmented generation (RAG) offers a promising way to provide grounded agricultural recommendations, yet it remains u...