Unverified50% confidenceSolutionExact time
The METHODNAME method fits a token–uncertainty mapping for each linguistic marker so that it best explains the actual correctness rate of the model's answers.
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10/4/2026
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UnverifiedAdding schema validation at the tool-calling stage constrains the uncertainty of model outputs to a controllable range.74% similarUnverifiedTraditional large language model evaluation centers on the accuracy of single-turn question answering, scoring the output answer against a reference answer after a question is given71% similarUnverifiedThe paper proposes a novel optimization-based algorithm (codenamed METHODNAME) that learns optimal uncertainty profiles directly from LLM outputs, rather than estimating uncertainty through repeated sampling.71% similarVerifiedWhen generating each token, large language models perform probabilistic sampling over all possible next words in the vocabulary, rather than deterministically selecting a unique answer.70% similarUnverifiedImplementing speculative decoding requires finding a balance between the inference speed of the draft model and its prediction accuracy.70% similar
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