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 126–150 of 209 papers

TitleStatusHype
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations—0
Unsupervised Text Generation by Learning from Search—0
Using character overlap to improve language transformation—0
Using Paraphrases and Lexical Semantics to Improve the Accuracy and the Robustness of Supervised Models in Situated Dialogue Systems—0
Vector-Quantized Prompt Learning for Paraphrase Generation—0
Controllable Paraphrase Generation with a Syntactic Exemplar—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
Metaphoric Paraphrase Generation—0
Modelling Events through Memory-based, Open-IE Patterns for Abstractive Summarization—0
Multi-Attribute Linguistic Tuning for Controlled Paraphrase Generation—0
Multilingual Paraphrase Generation For Bootstrapping New Features in Task-Oriented Dialog Systems—0
Multi-task Learning for Paraphrase Generation With Keyword and Part-of-Speech Reconstruction—0
Negative Lexically Constrained Decoding for Paraphrase Generation—0
Neural Clinical Paraphrase Generation with Attention—0
Neural-Driven Multi-criteria Tree Search for Paraphrase Generation—0
Neural-Driven Search-Based Paraphrase Generation—0
Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity?—0
Neural Machine Translation for Malayalam Paraphrase Generation—0
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Benchmark Results

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