running R code inside Python quickly transferring huge datasets between Python (NumPy/pandas/polars) and R without writing to disk interactively working in both languages at the same time ...
Abstract: Though quite challenging, training a deep neural network for automatically solving Math Word Problems (MWPs) has increasingly attracted attention due to its significance in investigating how ...
Abstract: Corruptions due to data perturbations and label noise are prevalent in the datasets from unreliable sources, which poses significant threats to model training. Despite existing efforts in ...
We introduce VeriStruct, a novel framework that extends AI-assisted automated verification from single functions to more complex data structure modules in Verus. VeriStruct employs a planner module to ...
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Official implementation of the paper Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection accepted at the 21st International Conference ...
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