3 papers
cs.LG2025
Quantum Doubly Stochastic Transformers
Jannis Born, Filip Skogh, Kahn Rhrissorrakrai +3
At the core of the Transformer, the softmax normalizes the attention matrix to be right stochastic. Previous research has shown that this often de-stabilizes training and that enfo…
cs.LG2024
Black-box Uncertainty Quantification Method for LLM-as-a-Judge
Nico Wagner, Michael Desmond, Rahul Nair +6
LLM-as-a-Judge is a widely used method for evaluating the performance of Large Language Models (LLMs) across various tasks. We address the challenge of quantifying the uncertainty…
cs.CL2024
Personalized Collaborative Fine-Tuning for On-Device Large Language Models
Nicolas Wagner, Dongyang Fan, Martin Jaggi
We explore on-device self-supervised collaborative fine-tuning of large language models with limited local data availability. Taking inspiration from the collaborative learning com…