activity
20242026
collaborators

11 papers

cs.SE2026

Does It Render Everywhere? A Study of Cross-Environment Compatibility in MLLM-Generated Webpages

Ziyun Guo, Jingyu Xiao, Yuqiang Sun +1

Multimodal Large Language Models (MLLMs) have been increasingly adopted to automate webpage generation from visual designs (e.g., screenshots). However, existing evaluations are li…

cs.SE2026

Semantic-Enhanced Automatic Refinement of Architecture Recovery Results Using LLMs

Yiran Zhang, Chengwei Liu, Yuqiang Sun +5

Understanding the architecture is crucial for effectively maintaining and managing large software systems. However, discrepancies often exist between the designed and implemented a…

cs.CR2026

Beyond Detection: Agentic Attack Synthesis and Simulation for Smart Contracts

Xianhao Zhang, Jing Sun, Zijian Zhang +4

Smart contract vulnerabilities pose severe financial risks, yet existing security tools largely stop at vulnerability detection, offering limited support for explaining whether rep…

cs.CR2026

Knowledge Over Parameters: Evolving Smart Contract Vulnerability Detection

Yuqiang Sun, Han Liu, Ying Li +4

Smart contract vulnerabilities are predominantly logic bugs whose detection requires structured, step-by-step procedural knowledge of attack patterns and contract semantics. Existi…

cs.CR2026

Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap

Feiyang Huang, Yuqiang Sun, Fan Zhang +3

Large Language Models (LLMs) have shown promising performance in software vulnerability detection, particularly after domain-specific Supervised Fine-Tuning (SFT). However, it rema…

cs.SE2026

From Docs to Descriptions: Smell-Aware Evaluation of MCP Server Descriptions

Peiran Wang, Ying Li, Yuqiang Sun +3

The Model Context Protocol (MCP) has rapidly become a de facto standard for connecting LLM-based agents with external tools via reusable MCP servers. In practice, however, server s…