Harness Learning nearly doubles unseen-task performance without weight updates
DanielKhashabi · x · 2026-10-01
A retweeted technical thread introduces Harness Learning: training a model to adapt to tasks it has never seen without updating weights at test time. The model learns to revise harnesses using execution feedback, then applies that skill to improve harnesses on unseen tasks while weights stay fixed.
- Motivation: improving agent harnesses takes experimentation; let the model learn from those revisions
- Method: train on execution feedback to revise harnesses, weights frozen
- Result: nearly double performance on challenging unseen reasoning and multihop QA tasks
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