The authors modify the acceptance stage of a self-evolving agent based on SkillOpt.
Statistical gates help self-editing agents avoid lasting performance regressions
SAGE accepts skill-document edits only when paired validation results provide reliable evidence that gains outweigh newly introduced failures.
Chinese Tech
Yihao Wang · Linhan Xia · Rui Liu · Zhaofeng Zhang · Hongyu Wu · Yang Yang · +3 more
Peking University · University of Oklahoma · Tencent · Imperial College London · University of Michigan
Research Digest··3 min read
Wang et al.
Why this paper
From Tencent and 7 others
In one line
SAGE uses per-item paired comparisons and one-sided paired tests to accept skill edits only when wins are statistically reliable, reducing regressions in self-evolving LLM agents.
What we could check
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- ✓Reports numbers on named benchmarks (4 benchmarks)
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