Abstract: Public health researchers are increasingly interested in using social media data to study health-related behaviors, but manually labeling this data can be labor-intensive and costly. This ...

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InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders InterPLM is a toolkit for extracting, analyzing, and visualizing interpretable features from protein ...

Abstract: In order to explore whether type annotations can help students improve the efficiency of Python program development, this paper designs and implements a comparative experiment. A total of 38 ...