Publications

Traces of Memorisation in Large Language Models for Code

Large language models have gained significant popularity because of their ability to generate human-like text and potential applications in various fields, such as Software…

Towards Safe, Secure, and Usable LLMs4Code

Large Language Models (LLMs) are gaining popularity in the field of Natural Language Processing (NLP) due to their remarkable accuracy in various NLP tasks. LLMs designed…

The (ab)use of Open Source Code to Train Large Language Models

In recent years, Large Language Models (LLMs) have gained significant popularity due to their ability to generate human-like text and their potential applications in various…

STACC: Code Comment Classification using SentenceTransformers

Code comments are a key resource for information about software artefacts. Depending on the use case, only some types of comments are useful. Thus, automatic approaches to…

Targeted Attack on GPT-Neo for the SATML Language Model Data Extraction Challenge

Previous work has shown that Large Language Models are susceptible to so-called data extraction attacks. This allows an attacker to extract a sample that was contained in…

Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binaries

Reverse engineering binaries is required to understand and analyse programs for which the source code is unavailable. Decompilers can transform the largely unreadable…