16 citations · 21 across the 18 of their papers we have counts for
3 papers · 1 filter
Dynamic Vocabulary Pruning in Early-Exit LLMs
Jort Vincenti, Karim Abdel Sadek, Joan Velja +2
Increasing the size of large language models (LLMs) has been shown to lead to better performance. However, this comes at the cost of slower and more expensive inference. Early-exit…
DuoDiff: Accelerating Diffusion Models with a Dual-Backbone Approach
Daniel Gallo Fernández, Răzvan-Andrei Matişan, Alejandro Monroy Muñoz +4
Diffusion models have achieved unprecedented performance in image generation, yet they suffer from slow inference due to their iterative sampling process. To address this, early-ex…
Fast yet Safe: Early-Exiting with Risk Control
Metod Jazbec, Alexander Timans, Tin Hadži Veljković +4
Scaling machine learning models significantly improves their performance. However, such gains come at the cost of inference being slow and resource-intensive. Early-exit neural net…