Jin-Yu Cai

GLOW: Graph-Language Co-Encoding for Agentic Workflow Performance Prediction

GLOW is proposed, a unified framework for AW performance prediction that combines the graph-structure modeling ability of GNNs with the topology-aware semantic encoding capability of LLMs and consistently outperforms state-of-the-art baselines in both prediction accuracy and ranking utility.