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Semantic Code Search for Smart Contracts
To make the model more focused on the key contextual information, we use a multi-head attention network to generate embeddings for code features.
A Bytecode-based Approach for Smart Contract Classification
Our experimental studies on over 3, 300 real-world Ethereum smart contracts show that our model can classify smart contracts without source code and has better performance than baseline models.
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