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arXiv Machine Learning By Will LeVine, Brendan Evers, Sam Saltwick, Abhay Venkatesh

RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement

Read the original on arXiv Machine Learning →

RubricRefine is a training‑free pre‑execution refinement method that generates task‑specific rubrics from tool documentation, scores candidate code against explicit contract checks, and iteratively repairs failures before execution. It achieves an average score of 0.86 across seven models on M3ToolEval without any execution attempts, outperforming prior inference‑time baselines while incurring lower latency. The approach shows consistent performance on single‑step API‑Bank tasks and maintains an advantage in multi‑turn settings on AppWorld, with its effectiveness tied to the quality of the supplied documentation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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