ScoreFlow uses a score-weighted variant of direct preference optimization to automatically generate and refine per-task LLM agent workflows, reporting an average 8.2% improvement over baselines on six benchmarks.
A general theoretical paradigm to understand learning from human preferences
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ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization
ScoreFlow uses a score-weighted variant of direct preference optimization to automatically generate and refine per-task LLM agent workflows, reporting an average 8.2% improvement over baselines on six benchmarks.