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About Paraphrase Generation With Deep RL
The document presents a new framework for paraphrase generation that uses deep reinforcement learning. It consists of a generator and an evaluator, both modeled as neural networks. The generator is trained first with cross-entropy loss and then fine-tuned with policy gradients using the evaluator as the reward signal. The evaluator is trained to judge whether two sentences are paraphrases, using either supervised learning or inverse reinforcement learning depending on the data available. Experimental results on two datasets show the proposed approach outperforms state-of-the-art methods in automatic and human evaluations.
Detailed Information
| Author: | ['Ashish Singh'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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