Sebastian Brarda


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Chargrid: Towards Understanding 2D Documents
Anoop R Katti | Christian Reisswig | Cordula Guder | Sebastian Brarda | Steffen Bickel | Johannes Höhne | Jean Baptiste Faddoul
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

We introduce a novel type of text representation that preserves the 2D layout of a document. This is achieved by encoding each document page as a two-dimensional grid of characters. Based on this representation, we present a generic document understanding pipeline for structured documents. This pipeline makes use of a fully convolutional encoder-decoder network that predicts a segmentation mask and bounding boxes. We demonstrate its capabilities on an information extraction task from invoices and show that it significantly outperforms approaches based on sequential text or document images.


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Sequential Attention: A Context-Aware Alignment Function for Machine Reading
Sebastian Brarda | Philip Yeres | Samuel Bowman
Proceedings of the 2nd Workshop on Representation Learning for NLP

In this paper we propose a neural network model with a novel Sequential Attention layer that extends soft attention by assigning weights to words in an input sequence in a way that takes into account not just how well that word matches a query, but how well surrounding words match. We evaluate this approach on the task of reading comprehension (on the Who did What and CNN datasets) and show that it dramatically improves a strong baseline—the Stanford Reader—and is competitive with the state of the art.