GRADE: Graph Representation of LLM Agent Dependency and Execution

תקציר מקורי באנגליתarXiv:2606.22741v2 Announce Type: replace Abstract: A trace records what an LLM agent did at each step. What is gained by also recording what each step relied on? GRADE represents a run as one typed graph: execution edges come free from the trace, and dependency edges are supplied, each graded observed, declared, or inferred. On six observed-dependency corpora spanning tool use, coding, and the web, we price the dependency layer against run size under a fixed logistic probe. Within corpus the layer adds failure-prediction signal on three corpora, though one increment disappears under task-grouped folds and another reverses under a cubic spline. In leave-one-corpus-out transfer the size-normalized dependency block stays above chance on every held-out corpus while run size inverts on two. Th