3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.CL2024★ 3 cited
Cycles of Thought: Measuring LLM Confidence through Stable Explanations
Evan Becker, Stefano Soatto
In many high-risk machine learning applications it is essential for a model to indicate when it is uncertain about a prediction. While large language models (LLMs) can reach and ev…
cs.AI2024
Meanings and Feelings of Large Language Models: Observability of Latent States in Generative AI
Tian Yu Liu, Stefano Soatto, Matteo Marchi +2
We tackle the question of whether Large Language Models (LLMs), viewed as dynamical systems with state evolving in the embedding space of symbolic tokens, are observable. That is,…
cs.LG2024
Heat Death of Generative Models in Closed-Loop Learning
Matteo Marchi, Stefano Soatto, Pratik Chaudhari +1
Improvement and adoption of generative machine learning models is rapidly accelerating, as exemplified by the popularity of LLMs (Large Language Models) for text, and diffusion mod…