Paraphrase Generation via Adversarial Penalizations
Paraphrase generation is an important problem in Natural Language Processing that has been addressed with neural network-based approaches recently. This paper presents an adversarial framework to address the paraphrase generation problem in English. Unlike previous methods, we employ the discriminator output as penalization instead of using policy gradients, and we propose a global discriminator to avoid the Monte-Carlo search. In addition, this work use and compare different settings of input representation. We compare our methods to some baselines in the Quora question pairs dataset. The results show that our framework is competitive against the previous benchmarks.
Code (0)
등록된 구현이 없습니다.
Tasks
Paraphrase GenerationSimilar Papers 제목 키워드 기반
DivGAN: Towards Diverse Paraphrase Generation via Diversified Generative Adversarial Network
Paraphrases refer to texts that convey the same meaning with different expression forms. Traditional seq2seq-based models on paraphrase generation mainly focus on the fidelity while ignoring the diversity of outputs. In …
DiversityGenerative Adversarial NetworkParaphrase GenerationImproving Paraphrase Detection with the Adversarial Paraphrasing Task
If two sentences have the same meaning, it should follow that they are equivalent in their inferential properties, i.e., each sentence should textually entail the other. However, many paraphrase datasets currently in wid…
Dataset GenerationParaphrase IdentificationSentenceAdversarial Example Generation with Syntactically Controlled Paraphrase Networks
We propose syntactically controlled paraphrase networks (SCPNs) and use them to generate adversarial examples. Given a sentence and a target syntactic form (e.g., a constituency parse), SCPNs are trained to produce a par…
DecoderSentenceSparse and low-rank multivariate Hawkes processes
We consider the problem of unveiling the implicit network structure of node interactions (such as user interactions in a social network), based only on high-frequency timestamps. Our inference is based on the minimizatio…
A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation
Paraphrase generation aims to generate semantically consistent sentences with different syntactic realizations. Most of the recent studies rely on the typical encoder-decoder framework where the generation process is det…
DecoderDiversityParaphrase GenerationSemantic Similarity+3