Zihang Zeng

AI-for-Science Low-code Platform with Bayesian Adversarial Multi-Agent Framework

Large Language Models (LLMs) demonstrate potentials for automating scientific code generation but face challenges in reliability, error propagation in multi-agent workflows, and evaluation in domains with ill-defined success metrics. We present a Bayesian adversarial multi-agent framework specifical…