134 citations · 198 across the 10 of their papers we have counts for
4 papers · 1 filter
Black-Box Adversarial Attacks on LLM-Based Code Completion
Slobodan Jenko, Niels Mündler, Jingxuan He +2
Modern code completion engines, powered by large language models (LLMs), assist millions of developers with their strong capabilities to generate functionally correct code. Due to…
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
Niels Mündler, Mark Niklas Müller, Jingxuan He +1
Rigorous software testing is crucial for developing and maintaining high-quality code, making automated test generation a promising avenue for both improving software quality and b…
Exploiting LLM Quantization
Kazuki Egashira, Mark Vero, Robin Staab +2
Quantization leverages lower-precision weights to reduce the memory usage of large language models (LLMs) and is a key technique for enabling their deployment on commodity hardware…
Instruction Tuning for Secure Code Generation
Jingxuan He, Mark Vero, Gabriela Krasnopolska +1
Modern language models (LMs) have gained widespread acceptance in everyday and professional contexts, particularly in programming. An essential procedure enabling this adoption is…