most citedAdversarial Attack Classification and Robustness Testing for Large Language Models for Code

4 citations · 4 across the 2 of their papers we have counts for

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cs.SE2026

Improving the Robustness of Large Language Models for Code Tasks via Fine-tuning with Perturbed Data

Yang Liu, Armstrong Foundjem, Xingfang Wu +2

Context: In the fast-paced evolution of software development, Large Language Models (LLMs) have become indispensable tools for tasks such as code generation, completion, analysis,…

cs.SE2025★ 4 cited

Adversarial Attack Classification and Robustness Testing for Large Language Models for Code

Yang Liu, Armstrong Foundjem, Foutse Khomh +1

Large Language Models (LLMs) have become vital tools in software development tasks such as code generation, completion, and analysis. As their integration into workflows deepens, e…