Recurrent Neural Networks (RNNs) have become a core component of modern intelligent software due to their strong ability to model temporal dependencies. As RNNs are increasingly deployed in safety-critical domains, ensuring their reliability is crucial. However, most existing testing techniques are designed for feedfor...
Xin-Yu Gao, Shuo-Xiao Zhang, Ming-Hui Wei et al.· 0 citations
Large language models (LLMs) have demonstrated great potential in code reasoning tasks, but their reasoning processes lack reliable verification mechanisms, making it difficult to ensure logical correctness. The Tree of Thoughts (ToT) framework improves reasoning by exploring multiple paths and employing backtracking,...
Hao-Liang Cheng, En-Yi Tang, Shuo-Xiao Zhang et al.· 0 citations
Deep learning (DL) techniques are increasingly integrated into traditional software systems, giving rise to hybrid AI-enabled systems that combine neural models with program logic. While these systems exhibit remarkable capabilities, their complex and heterogeneous architectures pose significant challenges for reliabil...
Xin-Yu Gao, Yang Feng, Yu-Chen Lu et al.· 0 citations
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