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PAC-CF: Calibrating Irreversible Frontier Pruning in LLM-Guided Search
LLM-guided search is usually adopted to solve complex tasks by ranking and pruning top-$K$ candidates based on evaluator scores. However, irreducible bias still exists even if popular methods, such as repeated sampling, are applied to reduce variance. Consequently, pruning may remove every continuat
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