Story · HF Daily Papers
Harness-Delta Attribution: Dissecting Gains From Harness Evolution (HF Daily Papers)
paper · Story page
An evaluation protocol that attributes harness-evolution gains to benchmark overfitting, test-time compute, and a residual.
In plain words
- Researchers developed a way to check why artificial intelligence assistants score better after their instructions and tools change.
- It checks whether better scores come from changes tailored to particular test questions or from letting the computer do more work.
- Across 21 cases with clear gains, tailoring to test questions explained 54% of the improvement on average.
- Any gains left over only show the most improvement that might carry over to unfamiliar tasks.
- Developers can use these checks to avoid overestimating how much a change will help users beyond the test.
Appeared in
- Most of a harness-evolution gain is overfitting and extra compute
Oct 22, 2026 · lead story
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