State University of New York at Stony Brook

Better datasets and tasks to evaluate the capabilities of machine reading models are needed. 
Proceed by describing a number of baselines, benchmarks and new models to evaluate against this paradigm.

For the reading comprehension task, the paper used 2 simple base line models, 2 symbolic matching models, and 4 RNN models.

Models

Hermann, K. M., Kocisky, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., & Blunsom, P. (2015). Teaching machines to read and comprehend. Advances in neural information processing systems, 28, 1693-1701.
https://arxiv.org/abs/1506.03340v3

Teaching Machines to Read and Comprehend

Symbolic Matching models

consists of 3 parts.
1. Attentive Reader
2. Impatient Reader
3. A two layer Deep LSTM Reader with the question encoded before the documents.

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