Empirical Characterization of Inference-Time Elicited Probability Transformations in Large Language Models 事件

Empirical Characterization of Inference-Time Elicited Probability Transformations in Large Language Models arXiv:2603.19262v2 Announce Type: replace Abstract: Large language models increasingly rely on inference-time procedures such as chain-of-thought reasoning, self-refinement, retrieval augmentation, and verifier-guided revision, yet the structure of elicited probability transformations under these procedures remains poorly understood. We study externally elicited probability assignments ove