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Models trained with Harness Learning are claimed to nearly double performance on challenging unseen tasks
A post describes training a model to revise agent harnesses using execution feedback. It says the model can then improve harnesses for unseen tasks while its weights stay fixed at test time.
TLDR
The author says Harness Learning trains models to revise agent harnesses using execution feedback, then apply that skill to unseen tasks without updating their weights at test time. Models trained this way nearly double their performance on challenging unseen reasoning and multihop question-answering tasks, the author claims.
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2 Sources, first seen 10h ago
