55 citations · 97 across the 29 of their papers we have counts for
10 papers · 1 filter
API-guided Dataset Synthesis to Finetune Large Code Models
Zongjie Li, Daoyuan Wu, Shuai Wang +1
Large code models (LCMs), pre-trained on vast code corpora, have demonstrated remarkable performance across a wide array of code-related tasks. Supervised fine-tuning (SFT) plays a…
SelfDefend: LLMs Can Defend Themselves against Jailbreaking in a Practical Manner
Xunguang Wang, Daoyuan Wu, Zhenlan Ji +7
Jailbreaking is an emerging adversarial attack that bypasses the safety alignment deployed in off-the-shelf large language models (LLMs) and has evolved into multiple categories: h…
PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generation
Ye Liu, Yue Xue, Daoyuan Wu +4
With recent advances in large language models (LLMs), this paper explores the potential of leveraging state-of-the-art LLMs,such as GPT-4, to transfer existing human-written proper…
Testing and Understanding Erroneous Planning in LLM Agents through Synthesized User Inputs
Zhenlan Ji, Daoyuan Wu, Pingchuan Ma +2
Agents based on large language models (LLMs) have demonstrated effectiveness in solving a wide range of tasks by integrating LLMs with key modules such as planning, memory, and too…
How Multi-Modal LLMs Reshape Visual Deep Learning Testing? A Comprehensive Study Through the Lens of Image Mutation
Liwen Wang, Yuanyuan Yuan, Ao Sun +4
Visual deep learning (VDL) systems have shown significant success in real-world applications like image recognition, object detection, and autonomous driving. To evaluate the relia…
Pre-trained Model-based Actionable Warning Identification: A Feasibility Study
Xiuting Ge, Chunrong Fang, Quanjun Zhang +8
Actionable Warning Identification (AWI) plays a pivotal role in improving the usability of static code analyzers. Currently, Machine Learning (ML)-based AWI approaches, which mainl…
LLMs Can Defend Themselves Against Jailbreaking in a Practical Manner: A Vision Paper
Daoyuan Wu, Shuai Wang, Yang Liu +1
Jailbreaking is an emerging adversarial attack that bypasses the safety alignment deployed in off-the-shelf large language models (LLMs). A considerable amount of research exists p…
Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications
Wei Ma, Daoyuan Wu, Yuqiang Sun +5
Smart contracts are decentralized applications built atop blockchains like Ethereum. Recent research has shown that large language models (LLMs) have potential in auditing smart co…
ACFIX: Guiding LLMs with Mined Common RBAC Practices for Context-Aware Repair of Access Control Vulnerabilities in Smart Contracts
Lyuye Zhang, Kaixuan Li, Kairan Sun +4
Smart contracts are susceptible to various security issues, among which access control (AC) vulnerabilities are particularly critical. While existing research has proposed multiple…
LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning
Yuqiang Sun, Daoyuan Wu, Yue Xue +5
Large language models (LLMs) have demonstrated significant potential in various tasks, including those requiring human-level intelligence, such as vulnerability detection. However,…