Add repeat-level variability statistics to reward profiling - #2474
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mpatel31415 wants to merge 18 commits into
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Add repeat-level variability statistics to reward profiling#2474mpatel31415 wants to merge 18 commits into
mpatel31415 wants to merge 18 commits into
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Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
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Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
…d-variability-statistics Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
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Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
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August 18, 2026 09:51
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
…ability-statistics' into mpatelka/add-variability-statistics Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
Signed-off-by: Martyna Patelka <mpatelka@nvidia.com>
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Issue this PR addresses
Related new bug
Adds a per-repeat statistics to reward profiling / aggregation, so a score can be
reported with a measure of how much it moves between whole runs rather than as
a bare point estimate.
What's new
repeat_level_metrics— one entry per(agent, repeat), computed when anagent has two or more completed repeats. Each entry carries
sample_count,missing_count, and per numeric field:mean,median,std(ddof=1),sem,min/max,p25/p75, and a 95% Student's-t confidence interval.Cross-repeat aggregates — the per-repeat means are summarized across repeats
and merged into
agent_metricsasmean_across_repeats/mean/{field},median_across_repeats/…,se_across_repeats/…, and the 95% CI bounds.Note
Per task across samples aggregates deliberately gets no CI — a per-task distribution over
repeated outcomes can't be assumed normal, and the CLT doesn't apply to raw
outcomes, so their computation / formula is benchmark and metric specific.