RESEARCHMonitorWATCHLIST
How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Research introduces evalstats, a method to correct false positives and statistical bias in small-sample LLM-as-a-judge evaluations.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 30 September 2026
- Collected by OneBench
- 1 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2609.35815v1 Announce Type: new Abstract: Researchers across academia increasingly base significance claims on LLM judge scores and small-sample AI evaluations. Yet without well-calibrated confidence intervals…
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