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SpanUQ reveals that span-level uncertainty quantification can enhance both the accuracy and efficiency of LLM outputs, outperforming existing methods by a factor of 10-20x.
Free-form Chain-of-Thought prompting actually *hurts* LLMs when it comes to structured function-calling tasks, but a guided-structured template approach boosts tool-use accuracy by up to 12%.
