Fuzzing is a highly effective automated testing method for uncovering software vulnerabilities. Despite advances in fuzzing techniques, many fuzzers still struggle with coverage plateaus caused by fuzz blockers, which limit their ability to discover deeper vulnerabilities. We introduce InsightQL, the first human-assist...
Wen-Tao Gao, Renata Borovica-Gajic, Sang Kil Cha et al.· Proceedings of the 41st IEEE...· 0 citations
Database management systems increasingly serve dynamic and exploratory workloads, yet many of their decisions still rely on low-level signals such as recency, frequency, and address locality. These signals capture how data was accessed, but not what is being examined or how an analytical focus evolves. We argue for tre...
Farzaneh Zirak, Kasper Overgaard Mortensen, F. Choudhury et al.· 0 citations
This work introduces RUBRIC, a generator-agnostic filtering framework that formulates synthetic sample selection as a quality-over-quantity optimization problem and shows that RUBRIC improves F1-macro and recall while maintaining comparable ROC-AUC across several generators.
Yan-Xuan Yu, Dong Liu, Shu Wang et al.· arXiv.org· 1 citation
A Spectral-Aware Feature Alignment module to unify feature dimensionality and align cross-domain semantics in a community-aware manner and a Graph Diffusion Tokenized Transformer that constructs hybrid token sequences from local and global structural contexts for Transformer encoding, and applies diffusion-based refine...
Mo Li, Zhaosong Zhao, Linlin Ding et al.· Annual International ACM SIG...· 0 citations
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