Amos Darko

Supplemental Materials for Benchmarking Retrieval-Augmented Large Language Models for Green Building Cost and Duration Prediction

Supplemental materials for a study benchmarking retrieval-augmented large language models for predicting green building project cost and duration. Forty-one configurations from Anthropic, Google and OpenAI, across their reasoning-effort settings, each predicted 20 held-out Hong Kong BEAM Plus projects three times (2,46...