3 papers
math.NA2026
Numerical stability analysis of large language models
Stanislav Budzinskiy, Wenyi Fang, Longbin Zeng +1
Transformers are the state-of-the-art architecture for large language models, and a key to their scalability is the strategic usage of low-precision arithmetic. We develop a mixed-…
cs.LG2026
LAMP: Look-Ahead Mixed-Precision Inference of Large Language Models
Stanislav Budzinskiy, Marian Gloser, Tolunay Yilmaz +5
Mixed-precision computations are a hallmark of the current stage of AI, driving the progress in large language models towards efficient, locally deployable solutions. This article…
cs.LG2026
Adaptivity Under Realizability Constraints: Comparing In-Context and Agentic Learning
Anastasis Kratsios, A. Martina Neuman, Philipp Petersen
We compare in-context learning with fixed queries and agentic learning with adaptive queries for uniform approximation of task families. We consider two settings: an unrestricted r…