CS224n PA4: Extending Match-LSTM
نویسندگان
چکیده
We propose two novel extensions to the Match-LSTM Boundary model for question answering on the SQuAD dataset. First we propose doing attention in the passage and question encoders. Second we propose adding a one-way conditional dependency between start-of-span and end-of-span prediction. In our evaluations, we show that these extensions result in a model that outperforms our implementation of vanilla Match-LSTM, suggesting a direction for future research.
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تاریخ انتشار 2017