Graph neural networks on assurance case graphs reach 0.76 ROC-AUC for link prediction and 0.94 F1 for distinguishing human from LLM-generated cases, with observed differences in hierarchical linking patterns.
Cross-modality mutual learning for enhancing smart contract vulnerability detection on bytecode
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
FAUDITOR is a specialized fuzzer that detected 220 zero-day monetarily exploitable vulnerabilities in smart contracts by combining finance-interface targeting, NLP from auditor reports, and self-learning.
BifrostRAG combines dual knowledge graphs with hybrid retrieval to improve multi-hop question answering on construction safety regulations, reporting 87.3% F1 on a custom dataset.
citing papers explorer
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Evaluating Assurance Cases as Text-Attributed Graphs for Structure and Provenance Analysis
Graph neural networks on assurance case graphs reach 0.76 ROC-AUC for link prediction and 0.94 F1 for distinguishing human from LLM-generated cases, with observed differences in hierarchical linking patterns.
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Capturing Monetarily Exploitable Vulnerability in Smart Contracts via Auditor Knowledge-Learning Fuzzing
FAUDITOR is a specialized fuzzer that detected 220 zero-day monetarily exploitable vulnerabilities in smart contracts by combining finance-interface targeting, NLP from auditor reports, and self-learning.
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Bridging Dual Knowledge Graphs for Multi-Hop Question Answering in Construction Safety
BifrostRAG combines dual knowledge graphs with hybrid retrieval to improve multi-hop question answering on construction safety regulations, reporting 87.3% F1 on a custom dataset.