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ASCT: Attentive Search over Counterfactual Trees for Credit Assignment in Agentic Reinforcement Learning
Terminal utility evaluates a complete agentic workflow, but learning requires credit for the decisions within it. We introduce Attentive Search over Counterfactual Trees (ASCT), a framework that turns training-time multi-step search into local action credit. At actor-visited states, an auxiliary tre
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