SAAG: Structured Agent Assessment and Grounding
A new diagnostic framework, SAAG, breaks down agent-calling evaluation into three sequential stages: registry conformance, structural completeness, and argument grounding. Experiments on a function-calling benchmark show that providing stage-specific feedback enables more precise argument selection and reduces hallucinated values compared to binary feedback. The framework also supports targeted self-repair of agent calls without exposing ground-truth values.
Why it matters: SAAG offers a more granular and actionable approach to diagnosing and improving agent-calling reliability, addressing limitations of traditional binary evaluation methods.
Full story at: arXiv AI/ML ↗