3 papers
cs.DC2026
Data Driven Optimization of GPU efficiency for Distributed LLM-Adapter Serving
Ferran Agullo, Joan Oliveras, Chen Wang +5
Large Language Model (LLM) adapters enable low-cost model specialization, but introduce complex caching and scheduling challenges in distributed serving systems where hundreds of a…
cs.PF2025
A Data-driven ML Approach for Maximizing Performance in LLM-Adapter Serving
Ferran Agullo, Joan Oliveras, Chen Wang +5
With the rapid adoption of Large Language Models (LLMs), LLM-adapters have become increasingly common, providing lightweight specialization of large-scale models. Serving hundreds…
cs.LG2025
FRIDA: Free-Rider Detection using Privacy Attacks
Pol G. Recasens, Ãdám Horváth, Alberto Gutierrez-Torre +3
Federated learning is increasingly popular as it enables multiple parties with limited datasets and resources to train a machine learning model collaboratively. However, similar to…