Slobodan Jenko — accepted AI-conference papers

2025

Black-Box Adversarial Attacks on LLM-Based Code Completion

Slobodan Jenko, Niels Mündler, Jingxuan He, Mark Vero, Martin Vechev

ICML 2025poster

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 this popularity, it is crucial to investigate the security implications of relying on LLM-based code completion. In this…

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2024

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Niels Mündler, Jingxuan He, Slobodan Jenko, Martin Vechev

ICLR 2024poster

Large language models (large LMs) are susceptible to producing text that contains hallucinated content. An important instance of this problem is self-contradiction, where the LM generates two contradictory sentences within the same context. In this work, we present a comprehensive investigation into…

Cited by 181 Source ↗PDF ↗code ↗Scholar ↗