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LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource Languages
To address this gap, we propose leveraging the potential of LLMs in the active learning loop for data annotation.
HyMo: Vulnerability Detection in Smart Contracts using a Novel Multi-Modal Hybrid Model
In this paper, we propose HyMo as a multi-modal hybrid deep learning model, which intelligently considers various input representations to consider multimodality and FastText word embedding technique, which represents each word as an n-gram of characters with BiGRU deep learning technique, as a sequence processing model that consists of two GRUs to achieve higher accuracy in smart contract vulnerability detection.
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