Paraphrase Generation System

A Paraphrase Generation System is a language generation system that implements a paraphrase generation algorithm to solve a paraphrase generation task.

• Context:
  • It can (typically) be a Data-Driven Paraphrase Generation System.
  • …
• Example(s):
  • a Neural Paraphrase Detection System.
  • …
• Counter-Example(s):
  • a Paraphrase Detection System.
  • a Summarization System.
• See: [[]].

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References

2016a

• (Bowman et al., 2016) ⇒ Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio. (2016). “Generating Sentences from a Continuous Space.” In: Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning, (CoNLL-2016).
  • https://github.com/kefirski/pytorch_RVAE based on (Bowman et al., 2016), using PyTorch.
  • https://github.com/Chung-I/Variational-Recurrent-Autoencoder-Tensorflow based on (Bowman et al., 2016), using TensorFlow.

2016b

• (Hasan et al., 2016) ⇒ Sadid A. Hasan, Kathy Lee, Vivek Datla, Ashequl Qadir, Joey Liu, and Oladimeji Farri. (2016). “Neural Paraphrase Generation with Stacked Residual LSTM Networks.” In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 2923-2934.
• https://github.com/iamaaditya/neural-paraphrase-generation

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