1 citations · 3 across the 10 of their papers we have counts for
11 papers
Confidence-Guided Protocol IR for LLM-Aided Security Protocol Modeling
Siqi Li, Yufan Cai, Hongshu Wang +3
Large language models offer a promising interface for translating natural-language protocol descriptions into formal security models, but their outputs remain difficult to trust wi…
Towards Fully Automated Medical Imaging Code Generation via Validation-based Context Engineering
Zixiao Zhao, Jing Sun, Zhe Hou +5
Large language models (LLMs) have demonstrated considerable promise in program generation for small-scale and conventional application development; however, they remain limited whe…
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…
Few-Shot Precise Event Spotting via Unified Multi-Entity Graph and Distillation
Zhaoyu Liu, Kan Jiang, Murong Ma +3
Precise event spotting (PES) aims to recognize fine-grained events at exact moments and has become a key component of sports analytics. This task is particularly challenging due to…
PAT-Agent: Autoformalization for Model Checking
Xinyue Zuo, Yifan Zhang, Hongshu Wang +4
Recent advances in large language models (LLMs) offer promising potential for automating formal methods. However, applying them to formal verification remains challenging due to th…
Adaptive Plan-Execute Framework for Smart Contract Security Auditing
Zhiyuan Wei, Jing Sun, Zijian Zhang +2
Large Language Models (LLMs) have shown great promise in code analysis and auditing; however, they still struggle with hallucinations and limited context-aware reasoning. We introd…
FSet: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Zhaoyu Liu, Kan Jiang, Murong Ma +3
Analyzing Fast, Frequent, and Fine-grained (F) events presents a significant challenge in video analytics and multi-modal LLMs. Current methods struggle to identify events that…
The Fusion of Large Language Models and Formal Methods for Trustworthy AI Agents: A Roadmap
Yedi Zhang, Yufan Cai, Xinyue Zuo +9
Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generat…
MaCTG: Multi-Agent Collaborative Thought Graph for Automatic Programming
Zixiao Zhao, Jing Sun, Zhe Hou +4
With the rapid advancement of Large Language Models (LLMs), LLM-based approaches have demonstrated strong problem-solving capabilities across various domains. However, in automatic…
FTSmartAudit: A Knowledge Distillation-Enhanced Framework for Automated Smart Contract Auditing Using Fine-Tuned LLMs
Zhiyuan Wei, Jing Sun, Zijian Zhang +2
The rapid growth of blockchain technology has driven the widespread adoption of smart contracts. However, their inherent vulnerabilities have led to significant financial losses. T…
Towards Large Language Model Aided Program Refinement
Yufan Cai, Zhe Hou, Xiaokun Luan +4
Program refinement involves correctness-preserving transformations from formal high-level specification statements into executable programs. Traditional verification tool support f…