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Found 2 papers, 2 papers with code
CodeMind: A Framework to Challenge Large Language Models for Code Reasoning
The first two evaluate models to predict the execution output of an arbitrary code or code the model could correctly synthesize.
Self-supervised Consensus Representation Learning for Attributed Graph
Self-supervised loss is designed to maximize the agreement of the embeddings of the same node in the topology graph and the feature graph.
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