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In that benchmark comparison, do you even have the sample size to distinguish two models, or are you making decisions based on statistical noise?
"Resolution Diagnostics for Paired LLM Evaluation" offers a simple check: a per-pair resolution ratio q = N/N* that flags when a displayed ranking sits below the resolution floor regardless of p-value.
arXiv: https://arxiv.org/abs/2605.30315v1
Outrider automatically matched this paper to our fork of lm-evaluation-harness and opened a PR implementing the diagnostic.
Configure the action to find new methods tailored to your repo: https://github.com/remyxai/outrider
"Resolution Diagnostics for Paired LLM Evaluation" offers a simple check: a per-pair resolution ratio q = N/N* that flags when a displayed ranking sits below the resolution floor regardless of p-value.
arXiv: https://arxiv.org/abs/2605.30315v1
Outrider automatically matched this paper to our fork of lm-evaluation-harness and opened a PR implementing the diagnostic.
Configure the action to find new methods tailored to your repo: https://github.com/remyxai/outrider
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