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TOPIC · ENTITY #20072

test-time scaling

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RESEARCH · 1 SOURCE · arXiv cs.AI

TEX: execution-driven cross-validation for test-time scaling of agents

TEX is a collaborative test-time scaling framework that parallelizes agents to generate tests and patches, cross-executing each test against every patch to form a K×K feedback matrix used for refinement without sharing verbose traces. Reported on arXiv (2610.27290v1), TEX reaches 86.4% on SWT-Bench Verified (a +9.0% gain over single-agent baselines) and shows that even random selection from TEX outputs (84.4%) exceeds the prior SOTA (84.0%).

7.0

RESEARCH · 1 SOURCE · arXiv cs.AI

Paper introduces Harness-Delta Attribution (HDA) to dissect gains from harness evolution

arXiv:2610.22466v1 introduces Harness-Delta Attribution (HDA), an evaluation protocol that decomposes performance gains from harness evolution into artifact-driven overfitting, test-time scaling, and a residual upper bound on potentially generalizable improvement. Applied to 11 executor models and three harness-evolution frameworks across math, coding, creativity, and agentic tasks, the study finds that overfitting and test-time scaling explain a large share of search-set gains (mean 54% and 14%, respectively), that gains often fail to transfer to held-out tasks, and that validation signals alone are insufficient to prevent overfitting.

7.0