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Improving Math Word Problems with Pre-trained Knowledge and Hierarchical Reasoning
Firstly, our pre-trained knowledge encoder aims at reasoning the MWP by using outside knowledge from the pre-trained transformer-based models.
AdaNAS: Adaptively Post-processing with Self-supervised Neural Architecture Search for Ensemble Rainfall Forecasts
Additionally, the proposed AdaNAS model is compared with other neural architecture search methods and previous studies.
SAIH: A Scalable Evaluation Methodology for Understanding AI Performance Trend on HPC Systems
In this paper, we propose a scalable evaluation methodology (SAIH) for analyzing the AI performance trend of HPC systems with scaling the problem sizes of customized AI applications.
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