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Stanford CS224N Project: Abstractive Text Summarization with RNNs and QRNNs

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2l-dr

tl-dr (abstractive text summarization), take 2

Example results

Actual headline: dpp chairman touts 'three direct links' with mainland china Generated headline: dpp chairman says china will improve ties with taiwan <\s>

Actual headline: two palestinians killed in gaza strip clash with israeli army (updates with toll downgraded by israel, adds jericho arrest) Generated headline: two palestinians killed in gaza strip <\s>

Why is it called 2l-dr?

We've tried tackling the problem of text summarization before (our intial attempt was calle tl-dr), and this is our second attempt.

Models

We implemented a GRU encoder-decoder model, and a QRNNenc + RNNdec model.

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Stanford CS224N Project: Abstractive Text Summarization with RNNs and QRNNs

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