Closed-Loop Agent Evaluation: Layered Measurement and Self-Calibration
Factual evidence
What the source reports
A new research paper proposes closed-loop evaluation to continuously measure and calibrate deployed AI agent performance under biased outcomes.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 6 November 2026
- Collected by OneBench
- 7 Nov 2026, 02:01 UK
Stored source excerpt
arXiv:2611.07051v1 Announce Type: cross Abstract: Once an agent is live, teams want to know whether it is doing its job, not just whether it throws…
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OneBench interpretation
Institutional assessment
So what
Static benchmarking fails for live enterprise agents; feedback-driven measurement improves post-deployment governance and reliability tracking.
Do what
Review agent performance monitoring methodology with teams responsible for model risk management.