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Found 3 papers, 1 papers with code
Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models
Unlike syntax errors, for which a compiler or interpreter can issue a message, logic errors can be subtle.
Comparing Code Explanations Created by Students and Large Language Models
In this paper, we explore the potential of LLMs in generating explanations that can serve as examples to scaffold students' ability to understand and explain code.
RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
Enhancing the generalization capability of deep neural networks to unseen domains is crucial for safety-critical applications in the real world such as autonomous driving.
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