Papers with Automatic workflow generation

    1 papers
    BayesFlow: A Probability Inference Framework for Meta-Agent Assisted Workflow Generation (2026.findings-eacl)

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    Challenge: Large Language Models (LLMs) have demonstrated remarkable generality, often solving tasks with a single carefully engineered prompt.
    Approach: They propose to cast automatic workflow generation as Bayesian inference over a posterior distribution on workflows and instantiate BayesFlow as Bayer-based workflow generation framework.
    Outcome: The proposed framework improves accuracy by 9 percentage points over baselines and 65 percentage points on pool-wide benchmarks.

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