Privacy in large language models: Attacks, defenses and future directions

H Li, Y Chen, J Luo, J Wang, H Peng, Y Kang… - arxiv preprint arxiv …, 2023‏ - arxiv.org
The advancement of large language models (LLMs) has significantly enhanced the ability to
effectively tackle various downstream NLP tasks and unify these tasks into generative …

Pitfalls in language models for code intelligence: A taxonomy and survey

X She, Y Liu, Y Zhao, Y He, L Li… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Modern language models (LMs) have been successfully employed in source code
generation and understanding, leading to a significant increase in research focused on …

Federated large language model: A position paper

C Chen, X Feng, J Zhou, J Yin, X Zheng - arxiv e-prints, 2023‏ - ui.adsabs.harvard.edu
Large scale language models (LLM) have received significant attention and found diverse
applications across various domains, but their development encounters challenges in real …

Security of Language Models for Code: A Systematic Literature Review

Y Chen, W Sun, C Fang, Z Chen, Y Ge, T Han… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Language models for code (CodeLMs) have emerged as powerful tools for code-related
tasks, outperforming traditional methods and standard machine learning approaches …

Django: Detecting trojans in object detection models via gaussian focus calibration

G Shen, S Cheng, G Tao, K Zhang… - Advances in …, 2024‏ - proceedings.neurips.cc
Object detection models are vulnerable to backdoor or trojan attacks, where an attacker can
inject malicious triggers into the model, leading to altered behavior during inference. As a …

A survey on large language models for software engineering

Q Zhang, C Fang, Y **e, Y Zhang, Y Yang… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Software Engineering (SE) is the systematic design, development, and maintenance of
software applications, underpinning the digital infrastructure of our modern mainworld. Very …

Robustness, security, privacy, explainability, efficiency, and usability of large language models for code

Z Yang, Z Sun, TZ Yue, P Devanbu, D Lo - arxiv preprint arxiv:2403.07506, 2024‏ - arxiv.org
Large language models for code (LLM4Code), which demonstrate strong performance (eg,
high accuracy) in processing source code, have significantly transformed software …

Vulnerabilities in ai code generators: Exploring targeted data poisoning attacks

D Cotroneo, C Improta, P Liguori… - Proceedings of the 32nd …, 2024‏ - dl.acm.org
AI-based code generators have become pivotal in assisting developers in writing software
starting from natural language (NL). However, they are trained on large amounts of data …

Ecosystem of large language models for code

Z Yang, J Shi, P Devanbu, D Lo - arxiv preprint arxiv:2405.16746, 2024‏ - arxiv.org
The availability of vast amounts of publicly accessible data of source code and the advances
in modern language models, coupled with increasing computational resources, have led to …

Occlusion-based Detection of Trojan-triggering Inputs in Large Language Models of Code

A Hussain, MRI Rabin, T Ahmed, MA Alipour… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Large language models (LLMs) are becoming an integrated part of software development.
These models are trained on large datasets for code, where it is hard to verify each data …