AI RESEARCH
Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices
arXiv CS.AI
•
ArXi:2605.00351v1 Announce Type: cross Root cause localization in cloud native microservice systems requires modeling complex service dependencies, irregular temporal dynamics, and heterogeneous observability data. We present HyperODE RCA, a unified framework that combines hypergraph attention learning, latent ordinary differential equations, and multimodal cross attention fusion for fine grained root cause analysis.