Cover Image

CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feng, Ruijun, Pearce, Hammond, Liguori, Pietro, Sui, Yulei
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection
by: Trad, Fouad, et al.
Published: (2025)

On Unified Prompt Tuning for Request Quality Assurance in Public Code Review
by: Chen, Xinyu, et al.
Published: (2024)

ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction Tuning
by: Wang, Xinyi, et al.
Published: (2025)

Automating the Correctness Assessment of AI-generated Code for Security Contexts
by: Cotroneo, Domenico, et al.
Published: (2023)

Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective
by: Gong, Jingzhi, et al.
Published: (2025)

Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation
by: Chu, Zhaoyang, et al.
Published: (2024)

Fine-Tuning Code Language Models to Detect Cross-Language Bugs
by: Li, Zengyang, et al.
Published: (2025)

PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injection
by: Cotroneo, Domenico, et al.
Published: (2025)

An Initial Exploration of Contrastive Prompt Tuning to Generate Energy-Efficient Code
by: Weidmann, Sophie, et al.
Published: (2026)

AI Code Generators for Security: Friend or Foe?
by: Natella, Roberto, et al.
Published: (2024)

MulVul: Retrieval-augmented Multi-Agent Code Vulnerability Detection via Cross-Model Prompt Evolution
by: Wu, Zihan, et al.
Published: (2026)

Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit
by: Wan, Yao, et al.
Published: (2023)

Integrating Symbolic Execution into the Fine-Tuning of Code-Generating LLMs
by: Sakharova, Marina, et al.
Published: (2025)

CoTune: Co-evolutionary Configuration Tuning
by: Xiong, Gangda, et al.
Published: (2025)

Enhancing AI-based Generation of Software Exploits with Contextual Information
by: Liguori, Pietro, et al.
Published: (2024)

Machine Learning Techniques for Python Source Code Vulnerability Detection
by: Farasat, Talaya, et al.
Published: (2024)

Repository-Aware File Path Retrieval via Fine-Tuned LLMs
by: Yanuganti, Vasudha, et al.
Published: (2025)

Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor
by: Gao, Weibo, et al.
Published: (2025)

Turbulence: Systematically and Automatically Testing Instruction-Tuned Large Language Models for Code
by: Honarvar, Shahin, et al.
Published: (2023)

Enhancing High-Quality Code Generation in Large Language Models with Comparative Prefix-Tuning
by: Jiang, Yuan, et al.
Published: (2025)

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity
by: Cotroneo, Domenico, et al.
Published: (2025)

Keeping Code-Aware LLMs Fresh: Full Refresh, In-Context Deltas, and Incremental Fine-Tuning
by: Sharma, Pradeep Kumar, et al.
Published: (2025)

Studying Vulnerable Code Entities in R
by: Zhao, Zixiao, et al.
Published: (2024)

DDPT: Diffusion-Driven Prompt Tuning for Large Language Model Code Generation
by: Li, Jinyang, et al.
Published: (2025)

CSA-Trans: Code Structure Aware Transformer for AST
by: Oh, Saeyoon, et al.
Published: (2024)

RTLRepoCoder: Repository-Level RTL Code Completion through the Combination of Fine-Tuning and Retrieval Augmentation
by: Wu, Peiyang, et al.
Published: (2025)

An Empirical Evaluation of LLM-Based Approaches for Code Vulnerability Detection: RAG, SFT, and Dual-Agent Systems
by: Saju, Md Hasan, et al.
Published: (2026)

Harnessing the Power of LLMs in Source Code Vulnerability Detection
by: Mahyari, Andrew A
Published: (2024)

Structure-Aware Corpus Construction and User-Perception-Aligned Metrics for Large-Language-Model Code Completion
by: Liu, Dengfeng, et al.
Published: (2025)

An Empirically-grounded tool for Automatic Prompt Linting and Repair: A Case Study on Bias, Vulnerability, and Optimization in Developer Prompts
by: Rzig, Dhia Elhaq, et al.
Published: (2025)

ECO: Enhanced Code Optimization via Performance-Aware Prompting for Code-LLMs
by: Kim, Su-Hyeon, et al.
Published: (2025)

Beyond Summaries: Structure-Aware Labeling of Code Changes with Large Language Models
by: Weiss, Bar, et al.
Published: (2026)

Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models
by: Zhuo, Terry Yue, et al.
Published: (2024)

Free and Customizable Code Documentation with LLMs: A Fine-Tuning Approach
by: Chakrabarty, Sayak, et al.
Published: (2024)

The Code Whisperer: LLM and Graph-Based AI for Smell and Vulnerability Resolution
by: Baqar, Mohammad, et al.
Published: (2026)

LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward
by: Islam, Nafis Tanveer, et al.
Published: (2024)

Instruction Tuning for Secure Code Generation
by: He, Jingxuan, et al.
Published: (2024)

Reasoning with LLMs for Zero-Shot Vulnerability Detection
by: Zibaeirad, Arastoo, et al.
Published: (2025)

Effective Code Membership Inference for Code Completion Models via Adversarial Prompts
by: Jiang, Yuan, et al.
Published: (2025)

Selection of Prompt Engineering Techniques for Code Generation through Predicting Code Complexity
by: Wang, Chung-Yu, et al.
Published: (2024)