Smart Contracts

MANDO-LLM: Heterogeneous Graph Transformers with Large Language Models for Smart Contract Vulnerability Detection

MANDO-LLM is a new framework for smart contract security that combines the semantic understanding of Large Language Models (LLMs) with the structural analysis of Heterogeneous …

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Nhat-Minh Nguyen
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MANDO-HGT: Heterogeneous Graph Transformers for Smart Contract Vulnerability Detection

The paper introduces MANDO-HGT, a framework designed to improve the accuracy and scalability of vulnerability detection in Ethereum smart contracts. By converting source code or …

Hoang h. nguyen
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MANDO-GURU: vulnerability detection for smart contract source code by heterogeneous graph embeddings

The paper introduces MANDO-GURU, a deep learning tool that utilizes heterogeneous graph attention neural networks on control-flow and call graphs to accurately detect smart …

Hoang h. nguyen
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MANDO: Multi-Level Heterogeneous Graph Embeddings for Fine-Grained Detection of Smart Contract Vulnerabilities

The paper introduces MANDO, a framework designed to overcome the limitations of existing heterogeneous graph techniques in handling complex, variable software graphs. It …

Hoang h. nguyen
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