Iterative Alternating Neural Attention for Machine Reading

We propose a novel neural attention architecture to tackle machine comprehension tasks, such as answering Cloze-style queries with respect to a document. Unlike previous models, we do not collapse the query into a single vector, instead we deploy an iterative alternating attention mechanism that allows a fine-grained exploration of both the query and the document... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Question Answering Children's Book Test AIA Accuracy-NE 72% # 4
Question Answering CNN / Daily Mail AIA CNN 76.1 # 5

Methods used in the Paper


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