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 91–100 of 209 papers

TitleStatusHype
Visual Information Guided Zero-Shot Paraphrase GenerationCode0
TD-ConE: An Information-Theoretic Approach to Assessing Parallel Text Generation Data—0
Continual Learning for Seq2Seq Generations with Transformer Calibration—0
Sampling from Discrete Energy-Based Models with Quality/Efficiency Trade-offs—0
SHCT: A Successively Hierarchical Conditional Transformer for Controllable Paraphrase Generation—0
Improving Paraphrase Generation models with machine translation generated pre-training—0
Power Norm Based Lifelong Learning for Paraphrase Generations—0
Are We Evaluating Paraphrase Generation Accurately?—0
Exploring Metaphoric Paraphrase GenerationCode0
Syntactically-Informed Unsupervised Paraphrasing with Non-Parallel DataCode0
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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