The authors start with an outer-loop optimization run that has already searched for a strong global harness.
Tailoring agent harnesses per task beats one-size-fits-all optimization
Turbo Harness reuses prior optimization traces to modify a global agent harness for each incoming task.
Top University
Tunyu Zhang · Hao Wang · Kai Xu · Dimitris N. Metaxas
Rutgers University · Red Hat AI Innovation · MIT-IBM Watson AI Lab
Research Digest··2 min read
Zhang et al.
Why this paper
From MIT-IBM Watson AI Lab and 2 others
In one line
Turbo Harness adapts global harnesses per instance using prior optimization artifacts, outperforming baselines across seven benchmarks.
What we could check
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- ·No stated limitations found
- ✓Reports numbers on named benchmarks
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