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Found 5 papers, 1 papers with code
Noise-Aware Training of Layout-Aware Language Models
Pre-training an extractor model on unlabeled instances of the target document type, followed by a fine-tuning step on human-labeled instances does not work in these scenarios, as it surpasses the maximum allowable training time allocated for the extractor.
Cross-Modal Entity Matching for Visually Rich Documents
This makes it difficult to contextualize the information retrieved from querying these documents and gather actionable insights from them.
Interpretable Multi-Headed Attention for Abstractive Summarization at Controllable Lengths
Abstractive summarization at controllable lengths is a challenging task in natural language processing.
Discovery of Driving Patterns by Trajectory Segmentation
We apply the segmentation approach on a real-word, rich dataset of personal car trajectories provided by a major insurance company based in Columbus, Ohio.
Characterizing Driving Context from Driver Behavior
Because of the increasing availability of spatiotemporal data, a variety of data-analytic applications have become possible.
