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Learning What to Skip: Counterfactual Credit Assignment for Efficient Multi-Agent LLM Workflows

arXiv:2609.30734v1 Announce Type: new Abstract: Multi-agent LLM workflows use planning, execution, verification, and summarization to improve task performance, yet the value of each component depends on the state already produced. Executing every component can waste computation or overwrite a corre…

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  1. 2026-09-28 04:00 · arXiv cs.AI
    Learning What to Skip: Counterfactual Credit Assignment for Efficient Multi-Agent LLM Workflows

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