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Open Information Extraction: A Review of Baseline Techniques, Approaches, and Applications
With the abundant amount of available online and offline text data, there arises a crucial need to extract the relation between phrases and summarize the main content of each document in a few words.
FuNToM: Functional Modeling of RF Circuits Using a Neural Network Assisted Two-Port Analysis Method
FuNToM leverages the two-port analysis method for modeling multiple topologies using a single main dataset and multiple small datasets.
MTrainS: Improving DLRM training efficiency using heterogeneous memories
In Deep Learning Recommendation Models (DLRM), sparse features capturing categorical inputs through embedding tables are the major contributors to model size and require high memory bandwidth.
Tablext: A Combined Neural Network And Heuristic Based Table Extractor
Today's popular state-of-the-art methods for table extraction struggle to adequately extract tables with machine-readable text and structural data.
