Harness^2: Recursive Agent Harnessing for an Open World
Published 19 October 2026
A new framework helps LLM agents improve their execution systems for unfamiliar tasks without ground-truth verifiers. It learns from task-specific edits and reuses this experience, improving performance by up to 11.8 percentage points across three professional benchmarks.
Read the original on arxiv.org →