2 papers
cs.LG2026
How Token Influence Decays with Distance: A Green-Function View of Trained Language Models
Matthias Brändel, Stephan Köhler, Oliver Rheinbach
We study how the next-token prediction of an autoregressive Transformer language model changes under small perturbations of earlier input token embeddings. Motivated by operator le…
cs.CE2026
Machine Learning Surrogate Modeling for Homogenization of Hyperelastic Materials with Boolean Microstructures
Matthias Brändel, Oliver Rheinbach
Data-driven surrogate models are an alternative to numerical homogenization of heterogeneous materials. In this contribution, a supervised learning approach is presented for predic…