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 81–90 of 209 papers

TitleStatusHype
Data Augmentation with Paraphrase Generation and Entity Extraction for Multimodal Dialogue System—0
Improving Paraphrase Generation models with machine translation generated pre-training—0
Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for New Features in Task-Oriented Dialog Systems—0
IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages—0
CoSe-Co: Text Conditioned Generative CommonSense Contextualizer—0
Investigating the use of Paraphrase Generation for Question Reformulation in the FRANK QA system—0
Automatic and Human-AI Interactive Text Generation—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
A Learning-Exploring Method to Generate Diverse Paraphrases with Multi-Objective Deep Reinforcement Learning—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