Who Verifies the Verifier? Co-Evolving Inspectable Graders with Self-Improving Agents
Factual evidence
What the source reports
Researchers propose co-evolving inspectable verifiers alongside agents to reduce reward hacking and shared LLM judge blind spots.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 9 October 2026
- Collected by OneBench
- 10 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2610.11464v1 Announce Type: cross Abstract: We changed the agent: did it actually get better? Every self-improving agent loop answers this hundreds of times, and every…
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OneBench interpretation
Institutional assessment
So what
LLM-as-a-judge approaches in agentic workflows risk hidden failure modes and reward hacking without deterministic, inspectable grading frameworks.
Do what
Review agent evaluation methodologies with model risk management teams to ensure LLM judges include auditable, rule-based verification components.