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cs.AI2026
Beyond Semantic Equivalence: Logical Graphs for LLM Uncertainty Quantification
Yanni Dong, Minghua Liu, Meilin Zhu +2
Large Language Models often produce confidently stated yet unreliable outputs, posing critical challenges for deployment in safety-sensitive applications. Existing uncertainty metr…
cs.AI2025
Shapley Uncertainty in Natural Language Generation
Meilin Zhu, Gaojie Jin, Xiaowei Huang +1
In question-answering tasks, determining when to trust the outputs is crucial to the alignment of large language models (LLMs). Kuhn et al. (2023) introduces semantic entropy as a…