8 citations · 12 across the 23 of their papers we have counts for
19 papers · 1 filter
Memoir: Learning, Verifying, and Evolving False-Positive Memories for Static Application Security Testing Tools
Shenyuan Guan, Qiaodan Hou, Yanjun Chen +4
Static Application Security Testing (SAST) tools have become indispensable in modern secure software devel- opment. However, these tools often generate false-positive (FP) alerts,…
Benchmarking Multimodal LLMs on Code Generation for Complex Interactive Webpages
Fan Wu, Lishuai Dong, Cuiyun Gao +4
Recent advancements in multimodal large language models (MLLMs) have achieved remarkable progress in multimodal reasoning and code generation, catalyzing a new paradigm for front-e…
Schedule-and-Calibrate: Utility-Guided Multi-Task Reinforcement Learning for Code LLMs
Yujia Chen, Yang Ye, Xiao Chu +2
Reinforcement learning (RL) with verifiable rewards has proven effective at post-training LLMs for coding, yet deploying separate task-specific specialists incurs costs that scale…
Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing
Chaozheng Wang, Zezhou Yang, Shuzheng Gao +7
Code editing constitutes a fundamental practice in software development, wherein developers modify existing codebases according to natural language requirements. Accurate code edit…
On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation
Jia Feng, Zhanyue Qin, Cuiyun Gao +4
Repository-level code intelligence tasks require large language models (LLMs) to process long, multi-file contexts. Such inputs introduce three challenges: crucial context can be o…
LLM-Based Test Case Generation in DBMS through Monte Carlo Tree Search
Yujia Chen, Yingli Zhou, Fangyuan Zhang +1
Database Management Systems (DBMSs) are fundamental infrastructure for modern data-driven applications, where thorough testing with high-quality SQL test cases is essential for ens…
SWE-Fuse: Empowering Software Agents via Issue-free Trajectory Learning and Entropy-aware RLVR Training
Xin-Cheng Wen, Binbin Chen, Haoxuan Lan +3
Large language models (LLMs) have transformed the software engineering landscape. Recently, numerous LLM-based agents have been developed to address real-world software issue fixin…
StriderSPD: Structure-Guided Joint Representation Learning for Binary Security Patch Detection
Qingyuan Li, Chenchen Yu, Chuanyi Li +4
Vulnerabilities severely threaten software systems, making the timely application of security patches crucial for mitigating attacks. However, software vendors often silently patch…
MLLM-Based UI2Code Automation Guided by UI Layout Information
Fan Wu, Cuiyun Gao, Shuqing Li +2
Converting user interfaces into code (UI2Code) is a crucial step in website development, which is time-consuming and labor-intensive. The automation of UI2Code is essential to stre…
Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware
Yujia Chen, Mingyu Chen, Cuiyun Gao +3
Application Programming Interfaces (APIs) are crucial in modern software development. Large Language Models (LLMs) assist in automated code generation but often struggle with API h…
EvalSVA: Multi-Agent Evaluators for Next-Gen Software Vulnerability Assessment
Xin-Cheng Wen, Jiaxin Ye, Cuiyun Gao +2
Software Vulnerability (SV) assessment is a crucial process of determining different aspects of SVs (e.g., attack vectors and scope) for developers to effectively prioritize effort…
Repository-Level Graph Representation Learning for Enhanced Security Patch Detection
Xin-Cheng Wen, Zirui Lin, Cuiyun Gao +3
Software vendors often silently release security patches without providing sufficient advisories (e.g., Common Vulnerabilities and Exposures) or delayed updates via resources (e.g.…
Smaller but Better: Self-Paced Knowledge Distillation for Lightweight yet Effective LCMs
Yujia Chen, Yang Ye, Zhongqi Li +2
Large code models (LCMs) have remarkably advanced the field of code generation. Despite their impressive capabilities, they still face practical deployment issues, such as high inf…
Bridge and Hint: Extending Pre-trained Language Models for Long-Range Code
Yujia Chen, Cuiyun Gao, Zezhou Yang +2
In the field of code intelligence, effectively modeling long-range code poses a significant challenge. Existing pre-trained language models (PLMs) such as UniXcoder have achieved r…
VulEval: Towards Repository-Level Evaluation of Software Vulnerability Detection
Xin-Cheng Wen, Xinchen Wang, Yujia Chen +3
Deep Learning (DL)-based methods have proven to be effective for software vulnerability detection, with a potential for substantial productivity enhancements for detecting vulnerab…
SCALE: Constructing Structured Natural Language Comment Trees for Software Vulnerability Detection
Xin-Cheng Wen, Cuiyun Gao, Shuzheng Gao +2
Recently, there has been a growing interest in automatic software vulnerability detection. Pre-trained model-based approaches have demonstrated superior performance than other Deep…
APIGen: Generative API Method Recommendation
Yujia Chen, Cuiyun Gao, Muyijie Zhu +3
Automatic API method recommendation is an essential task of code intelligence, which aims to suggest suitable APIs for programming queries. Existing approaches can be categorized i…
Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning
Xin-Cheng Wen, Cuiyun Gao, Xinchen Wang +3
Recent years have witnessed a growing focus on automated software vulnerability detection. Notably, deep learning (DL)-based methods, which employ source code for the implicit acqu…
SliceLocator: Locating Vulnerable Statements with Graph-based Detectors
Baijun Cheng, Kailong Wang, Cuiyun Gao +5
Vulnerability detection is a crucial component in the software development lifecycle. Existing vulnerability detectors, especially those based on deep learning (DL) models, have ac…