most citedTraces of Memorisation in Large Language Models for Code

30 citations · 42 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR202430 cited

Traces of Memorisation in Large Language Models for Code

Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen

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 Enginee…

cs.SE20231 cited

STACC: Code Comment Classification using SentenceTransformers

Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen

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 classify…

cs.SE20231 cited

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

Ali Al-Kaswan, Maliheh Izadi

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 fields…

cs.CL20235 cited

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

Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen

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 the train…

cs.CR20235 cited

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

Ali Al-Kaswan, Toufique Ahmed, Maliheh Izadi +3

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