Auditing the Judge: Internal Signals for LLM Reasoning Assurance
Factual evidence
What the source reports
Researchers propose using attention-head probes alongside verdict tokens to audit LLM self-judgment and reduce residual model error.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 11 November 2026
- Collected by OneBench
- 12 Nov 2026, 02:02 UK
- Original headline
- Auditing the Judge: Internal Signals for LLM Reasoning Assurance ↗
Stored source excerpt
arXiv:2611.14323v1 Announce Type: new Abstract: Language-model systems use self-judgment to decide which answers to release, review, or recompute. Because intervention is costly, an assurance score…
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OneBench interpretation
Institutional assessment
So what
Combining internal probe signals with standard self-judgment scores improves confidence calibration and automated error filtering in production LLM workflows.
Do what
Review internal probe methodologies with the model risk team when evaluating automated verification mechanisms for high-consequence deployment pipelines.