3 papers
cs.SE2026
Do LLMs Favor Their Providers? Measuring Vertical Integration Bias in Code Generation
Melih Catal, Alex Wolf, Tiago Ferreiro Matos +2
Large Language Models (LLMs) have become an integral part of software development, especially with the advent of agentic capabilities. Yet, many frontier LLMs are affiliated with s…
cs.SE2025
Towards Privacy-Preserving Code Generation: Differentially Private Code Language Models
Melih Catal, Pooja Rani, Harald C. Gall
Large language models specialized for code (CodeLLMs) have demonstrated remarkable capabilities in generating code snippets, documentation, and test cases. However, despite their p…
cs.CV2024
AdvSecureNet: A Python Toolkit for Adversarial Machine Learning
Melih Catal, Manuel Günther
Machine learning models are vulnerable to adversarial attacks. Several tools have been developed to research these vulnerabilities, but they often lack comprehensive features and f…