Papers with multi-head self attention
Transformer and seq2seq model for Paraphrase Generation (D19-56)
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| Challenge: | Existing methods for generating paraphrases fall into one of these broad categories -rule-based, seq2seq, deep generative models and a varied combination. |
| Approach: | They propose a framework that combines transformer and sequence-to-sequence models for better quality of generated paraphrases. |
| Outcome: | The proposed framework improves on two datasets-QUORA and MSCOCO using transformer and sequence-to-sequence models. |