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cs.LG2025
On Convolutions, Intrinsic Dimension, and Diffusion Models
Kin Kwan Leung, Rasa Hosseinzadeh, Gabriel Loaiza-Ganem
The manifold hypothesis asserts that data of interest in high-dimensional ambient spaces, such as image data, lies on unknown low-dimensional submanifolds. Diffusion models (DMs) -…
cs.LG2025
Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems
Brendan Leigh Ross, Noël Vouitsis, Atiyeh Ashari Ghomi +8
Although large language models (LLMs) are becoming increasingly capable of solving challenging real-world tasks, accurately quantifying their uncertainty remains a critical open pr…