Gated End-to-End Memory Networks

@inproceedings{Liu2017GatedEM,
  title={Gated End-to-End Memory Networks},
  author={Fei Liu and Julien Perez},
  booktitle={EACL},
  year={2017}
}
Machine reading using differentiable reasoning models has recently shown remarkable progress. In this context, End-to-End trainable Memory Networks (MemN2N) have demonstrated promising performance on simple natural language based reasoning tasks such as factual reasoning and basic deduction. However, other tasks, namely multi-fact question-answering, positional reasoning or dialog related tasks, remain challenging particularly due to the necessity of more complex interactions between the memory… Expand
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