SOTAVerified

Paraphrase Generation

Paraphrase Generation involves transforming a natural language sentence to a new sentence, that has the same semantic meaning but a different syntactic or lexical surface form.

Papers

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Showing 176–200 of 209 papers

TitleStatusHype
GCPG: A General Framework for Controllable Paraphrase Generation—0
Generating Paraphrases with Lean Vocabulary—0
Generating Syntactic Paraphrases—0
Generative Pre-training for Paraphrase Generation by Representing and Predicting Spans in Exemplars—0
Gradient-guided Unsupervised Lexically Constrained Text Generation—0
How to Ask Good Questions? Try to Leverage Paraphrases—0
How to make words with vectors: Phrase generation in distributional semantics—0
IIIT-H: A Corpus-Driven Co-occurrence Based Probabilistic Model for Noun Compound Paraphrasing—0
Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing—0
Improving Large-scale Paraphrase Acquisition and Generation—0
Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention—0
Improving Paraphrase Generation models with machine translation generated pre-training—0
IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages—0
Investigating the use of Paraphrase Generation for Question Reformulation in the FRANK QA system—0
Joint Learning of a Dual SMT System for Paraphrase Generation—0
Keep the Primary, Rewrite the Secondary: A Two-Stage Approach for Paraphrase Generation—0
Label Dependent Deep Variational Paraphrase Generation—0
Rethinking and Improving Natural Language Generation with Layer-Wise Multi-View Decoding—0
Learning Structural Information for Syntax-Controlled Paraphrase Generation—0
Learning to Adapt to Low-Resource Paraphrase Generation—0
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation—0
Learning to Selectively Learn for Weakly Supervised Paraphrase Generation with Model-based Reinforcement Learning—0
Leveraging Crowdsourcing for Paraphrase Recognition—0
Metaphorical Paraphrase Generation: Feeding Metaphorical Language Models with Literal Texts—0
Metaphor: A Computational Perspective by Tony Veale, Ekaterina Shutova and Beata Beigman Klebanov—0
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All datasetsParalexQuora Question PairsMSCOCO

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HRQ-VAEiBLEU24.93—Unverified
2SeparatoriBLEU14.84—Unverified
#ModelMetricClaimedVerifiedStatus
1HRQ-VAEiBLEU18.42—Unverified
2SeparatoriBLEU5.84—Unverified
#ModelMetricClaimedVerifiedStatus
1HRQ-VAEBLEU27.9—Unverified