62% vs 58% on the Same Benchmark: How Many Tasks Before the Gap Means Anything?
Two teams run the same agent benchmark on the same model with the same scaffold. Team A runs 100 tasks and reports 62%. Team B runs 250 and reports 58%. Both publish their task lists and pass rates. Neither is cheating. Is the four-point gap real, or did the two teams stop at different points? Wei-Jung Huang's paper (arXiv:2607.12338, 14 July 2026, KDD 2026 Agentic AI Evaluation and…
A recent paper demonstrates that the difference between 62% and 58% benchmark scores can be misleading due to how many tasks are evaluated. Researchers used replay techniques to examine task order and decision points rather than running new models. They analyzed four benchmarks - AppWorld, tau-bench, SWE-bench Verified, and SWE-bench Lite - and found that the gap between scores can vary depending on the number of tasks evaluated and the rules governing the decision-making process.
The paper highlights the importance of considering factors such as task selection, coverage rules, and the treatment of unresolved comparisons when interpreting benchmark results.
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