1 citations · 1 across the 4 of their papers we have counts for
6 papers
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…
Optimistic Dual Averaging Unifies Modern Optimizers
Thomas Pethick, Wanyun Xie, Roman Machacek +1
We introduce SODA, a generalization of Optimistic Dual Averaging, which provides a common perspective on state-of-the-art optimizers like Muon, Lion, AdEMAMix and NAdam, showing th…
On the Role of Batch Size in Stochastic Conditional Gradient Methods
Rustem Islamov, Roman Machacek, Aurelien Lucchi +3
We study the role of batch size in stochastic conditional gradient methods under a -Kurdyka-Łojasiewicz (-KL) condition. Focusing on momentum-based stochastic conditional gra…
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…
The Impact of Fine-tuning Large Language Models on Automated Program Repair
Roman Macháček, Anastasiia Grishina, Max Hort +1
Automated Program Repair (APR) uses various tools and techniques to help developers achieve functional and error-free code faster. In recent years, Large Language Models (LLMs) hav…
Explaining GitHub Actions Failures with Large Language Models: Challenges, Insights, and Limitations
Pablo Valenzuela-Toledo, Chuyue Wu, Sandro Hernandez +4
GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupt…