Author

R. Gupta

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#artificial intelligence Preprint Oct 2026

Runtime Control for AI Agents: Closing the Evaluation--Execution Gap in Operational Workflows

A state-bound runtime assurance layer that separates probabilistic measurement from deterministic adjudication, binds an execution allowance to the decision-relevant basis of an approval, invalidates that allowance after relevant logged changes, and rechecks admissibility at dispatch distinguishes the continued validit...

Jayesh Bhadane, Ramachandra Yerramsetti, Rajesh Gupta et al. · 0 citations

#artificial intelligence Review Sep 2026

Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows

A provenance-aware runtime architecture is introduced that evaluates policies over complete execution traces, recomputing guarded quantities from raw provenance rather than the pipeline's derived representation, and shows that the correct repair for each class is dictated by where the guarded quantity mutates.

Ashwini Kurady, S. Grandhi, Rajesh Gupta et al. · arXiv.org · 1 citation