Rethinking the Capability of Fine-Tuned Language Models for Automated Vulnerability Repair
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Woorim, Kwak, Yeongjun, Yu, Miseon, Kim, Kyeongmin, Lee, Younghan, Moon, Hyungon, Paek, Yunheung |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Precise Extraction of Deep Learning Models via Side-Channel Attacks on Edge/Endpoint Devices
by: Lee, Younghan, et al.
Published: (2024)
by: Lee, Younghan, et al.
Published: (2024)
VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification
by: Cho, Yungi, et al.
Published: (2024)
by: Cho, Yungi, et al.
Published: (2024)
Exploring Parameter-Efficient Fine-Tuning of Large Language Model on Automated Program Repair
by: Li, Guochang, et al.
Published: (2024)
by: Li, Guochang, et al.
Published: (2024)
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
by: Lee, Younghan, et al.
Published: (2024)
by: Lee, Younghan, et al.
Published: (2024)
Patch Validation in Automated Vulnerability Repair
by: Yu, Zheng, et al.
Published: (2026)
by: Yu, Zheng, et al.
Published: (2026)
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
by: wang, Dong, et al.
Published: (2025)
by: wang, Dong, et al.
Published: (2025)
Enhanced Automated Code Vulnerability Repair using Large Language Models
by: de-Fitero-Dominguez, David, et al.
Published: (2024)
by: de-Fitero-Dominguez, David, et al.
Published: (2024)
VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities
by: Wang, Weizhe, et al.
Published: (2025)
by: Wang, Weizhe, et al.
Published: (2025)
SoK: Automated Vulnerability Repair: Methods, Tools, and Assessments
by: Hu, Yiwei, et al.
Published: (2025)
by: Hu, Yiwei, et al.
Published: (2025)
LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models
by: Fakih, Mohamad, et al.
Published: (2025)
by: Fakih, Mohamad, et al.
Published: (2025)
Fine-Tuning Models for Automated Code Review Feedback
by: Kumar, Smitha S, et al.
Published: (2026)
by: Kumar, Smitha S, et al.
Published: (2026)
Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation
by: Pornprasit, Chanathip, et al.
Published: (2024)
by: Pornprasit, Chanathip, et al.
Published: (2024)
There are More Fish in the Sea: Automated Vulnerability Repair via Binary Templates
by: Lin, Bo, et al.
Published: (2024)
by: Lin, Bo, et al.
Published: (2024)
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair
by: Khan, Zanis Ali, et al.
Published: (2025)
by: Khan, Zanis Ali, et al.
Published: (2025)
Root-Cause-Driven Automated Vulnerability Repair
by: Wang, Hulin, et al.
Published: (2026)
by: Wang, Hulin, et al.
Published: (2026)
Automated Test Case Repair Using Language Models
by: Yaraghi, Ahmadreza Saboor, et al.
Published: (2024)
by: Yaraghi, Ahmadreza Saboor, et al.
Published: (2024)
Adapting Knowledge Prompt Tuning for Enhanced Automated Program Repair
by: Cai, Xuemeng, et al.
Published: (2025)
by: Cai, Xuemeng, et al.
Published: (2025)
Defects4C: Benchmarking Large Language Model Repair Capability with C/C++ Bugs
by: Wang, Jian, et al.
Published: (2025)
by: Wang, Jian, et al.
Published: (2025)
Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
VulKey: Automated Vulnerability Repair Guided by Domain-Specific Repair Patterns
by: Li, Jia, et al.
Published: (2026)
by: Li, Jia, et al.
Published: (2026)
Multi-LLM Collaboration + Data-Centric Innovation = 2x Better Vulnerability Repair
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
PAFT: Preservation Aware Fine-Tuning for Minimal-Edit Program Repair
by: Yang, Boyang, et al.
Published: (2026)
by: Yang, Boyang, et al.
Published: (2026)
A Systematic Literature Review on Large Language Models for Automated Program Repair
by: Zhang, Quanjun, et al.
Published: (2024)
by: Zhang, Quanjun, et al.
Published: (2024)
Automated Repair of C Programs Using Large Language Models
by: Farzandway, Mahdi, et al.
Published: (2025)
by: Farzandway, Mahdi, et al.
Published: (2025)
Exploring Generalizable Automated Program Repair with Large Language Models
by: Campos, Viola, et al.
Published: (2025)
by: Campos, Viola, et al.
Published: (2025)
Empirical Evaluation of Large Language Models in Automated Program Repair
by: Sun, Jiajun, et al.
Published: (2025)
by: Sun, Jiajun, et al.
Published: (2025)
Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models
by: Guo, Hanyang, et al.
Published: (2025)
by: Guo, Hanyang, et al.
Published: (2025)
Rethinking Legal Compliance Automation: Opportunities with Large Language Models
by: Hassani, Shabnam, et al.
Published: (2024)
by: Hassani, Shabnam, et al.
Published: (2024)
Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap
by: Huang, Feiyang, et al.
Published: (2026)
by: Huang, Feiyang, et al.
Published: (2026)
Well Begun is Half Done: Location-Aware and Trace-Guided Iterative Automated Vulnerability Repair
by: Ye, Zhenlei, et al.
Published: (2025)
by: Ye, Zhenlei, et al.
Published: (2025)
Revisiting Unnaturalness for Automated Program Repair in the Era of Large Language Models
by: Yang, Aidan Z. H., et al.
Published: (2024)
by: Yang, Aidan Z. H., et al.
Published: (2024)
EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution
by: Hu, Haichuan, et al.
Published: (2026)
by: Hu, Haichuan, et al.
Published: (2026)
Boosting Redundancy-based Automated Program Repair by Fine-grained Pattern Mining
by: Jiang, Jiajun, et al.
Published: (2023)
by: Jiang, Jiajun, et al.
Published: (2023)
RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
by: Silva, André, et al.
Published: (2023)
by: Silva, André, et al.
Published: (2023)
A Case Study of LLM for Automated Vulnerability Repair: Assessing Impact of Reasoning and Patch Validation Feedback
by: Kulsum, Ummay, et al.
Published: (2024)
by: Kulsum, Ummay, et al.
Published: (2024)
Vul-R2: A Reasoning LLM for Automated Vulnerability Repair
by: Wen, Xin-Cheng, et al.
Published: (2025)
by: Wen, Xin-Cheng, et al.
Published: (2025)
A Deep Dive into Large Language Models for Automated Bug Localization and Repair
by: Hossain, Soneya Binta, et al.
Published: (2024)
by: Hossain, Soneya Binta, et al.
Published: (2024)
Hybrid Automated Program Repair by Combining Large Language Models and Program Analysis
by: Li, Fengjie, et al.
Published: (2024)
by: Li, Fengjie, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning with Attributed Patch Semantic Graph for Automated Patch Correctness Assessment
by: Yang, Zhenyu, et al.
Published: (2025)
by: Yang, Zhenyu, et al.
Published: (2025)
Security Vulnerability Detection with Multitask Self-Instructed Fine-Tuning of Large Language Models
by: Yang, Aidan Z. H., et al.
Published: (2024)
by: Yang, Aidan Z. H., et al.
Published: (2024)
Similar Items
-
Precise Extraction of Deep Learning Models via Side-Channel Attacks on Edge/Endpoint Devices
by: Lee, Younghan, et al.
Published: (2024) -
VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification
by: Cho, Yungi, et al.
Published: (2024) -
Exploring Parameter-Efficient Fine-Tuning of Large Language Model on Automated Program Repair
by: Li, Guochang, et al.
Published: (2024) -
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
by: Lee, Younghan, et al.
Published: (2024) -
Patch Validation in Automated Vulnerability Repair
by: Yu, Zheng, et al.
Published: (2026)