Qiangqiang Dai

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation

OpenRTAG provides a standardized testbed for understanding robustness in TAG learning under realistic low-quality settings and systematically evaluates scenario validity and model sensitivity, compares traditional GNNs, LLM-GNNs, and a representative GFM, and investigates the effectiveness, efficiency, and robustness of scenario-matched baselines.