3 papers
cs.CR2026
Fetch Me If You Can: A Comprehensive Analysis of Fetch Metadata
Pedro Bernardo, Alex Ploner, Marco Squarcina +2
Effective server-side defenses against cross-site attacks depend on understanding the context in which browser requests are generated. However, servers often lack the information n…
cs.LG2025
EBGAN-MDN: An Energy-Based Adversarial Framework for Multi-Modal Behavior Cloning
Yixiao Li, Julia Barth, Thomas Kiefer +1
Multi-modal behavior cloning faces significant challenges due to mode averaging and mode collapse, where traditional models fail to capture diverse input-output mappings. This prob…
cs.LG2025
Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Ahmad Fraij, Sam Dauncey
Data scarcity drives the need for more sample-efficient large language models. In this work, we use the double descent phenomenon to holistically compare the sample efficiency of d…