Dream2Discern: Learning from Hard Latent Variants for Runtime Failure Prediction in Multi-Agent Systems.

arXiv:2610.16071v1 Announce Type: cross Abstract: Reliable deployment of LLM-based multi-agent systems calls for runtime auditors that predict terminal outcomes from observed execution prefixes. These auditors typically learn from a limited corpus of trajector