RealVuln benchmark finds security-specialized scanners outperform general-purpose LLMs and rule-based SAST tools on hand-labeled vulnerable Python code under F3 scoring, with all artifacts released.
Teo, Yiling Lou, Yebo Feng, Chong Wang, and Dinil Mon Divakaran
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ReasonVul deploys three LLM agents with independent analysis and structured debate to achieve 40% PairAcc and 72.52% F1 on PrimeVul, outperforming baselines by 81% in PairAcc.
UBRI case study abstracts recurring blockchain design tensions into a framework linking academic research to deployment constraints and policy adaptation.
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RealVuln: Benchmarking Rule-Based, General-Purpose LLM, and Security-Specialized Scanners on Real-World Code
RealVuln benchmark finds security-specialized scanners outperform general-purpose LLMs and rule-based SAST tools on hand-labeled vulnerable Python code under F3 scoring, with all artifacts released.
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Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection
ReasonVul deploys three LLM agents with independent analysis and structured debate to achieve 40% PairAcc and 72.52% F1 on PrimeVul, outperforming baselines by 81% in PairAcc.
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Systematizing Blockchain Research Themes and Design Patterns: Insights from the University Blockchain Research Initiative (UBRI)
UBRI case study abstracts recurring blockchain design tensions into a framework linking academic research to deployment constraints and policy adaptation.