mlsanityData to 7 Oct 2026

Quality Controlled Paraphrase Generation

arXiv 2203.10940 ↗First posted 21 Mar 2022cs.CLcited by 31

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Abstract (arXiv)

Paraphrase generation has been widely used in various downstream tasks. Most tasks benefit mainly from high quality paraphrases, namely those that are semantically similar to, yet linguistically diverse from, the original sentence. Generating high-quality paraphrases is challenging as it becomes increasingly hard to preserve meaning as linguistic diversity increases. Recent works achieve nice results by controlling specific aspects of the paraphrase, such as its syntactic tree. However, they do not allow to directly control the quality of the generated paraphrase, and suffer from low flexibility and scalability. Here we propose QCPG, a quality-guided controlled paraphrase generation model, that allows directly controlling the quality dimensions. Furthermore, we suggest a method that given a sentence, identifies points in the quality control space that are expected to yield optimal generated paraphrases. We show that our method is able to generate paraphrases which maintain the original meaning while achieving higher diversity than the uncontrolled baseline. The models, the code, and the data can be found in https://github.com/IBM/quality-controlled-paraphrase-generation.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). Builds on 23 of its 43 references that are in the map. First posted on arXiv 21 Mar 2022.

Builds on

23 of 43 references.

References · 23

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  5. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
  6. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
  7. 2018Texygen: A Benchmarking Platform for Text Generation Modelscited by 484
  8. 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 394
  9. 2018Adversarial Example Generation with Syntactically Controlled Paraphrase Networkscited by 282
  10. 2018The Natural Language Decathlon: Multitask Learning as Question Answeringcited by 235
  11. 2018QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehensioncited by 164
  12. 2019Generating Sentences from Disentangled Syntactic and Semantic Spacescited by 59
11 more
  1. 2020Neural Syntactic Preordering for Controlled Paraphrase Generationcited by 56
  2. 2017A Deep Generative Framework for Paraphrase Generationcited by 54
  3. 2019Controllable Paraphrase Generation with a Syntactic Exemplarcited by 44
  4. 2018Effective Parallel Corpus Mining using Bilingual Sentence Embeddingscited by 39
  5. 2019Unsupervised Paraphrasing by Simulated Annealingcited by 37
  6. 2020Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic Diversitycited by 35
  7. 2019Decomposable Neural Paraphrase Generationcited by 30
  8. 2020Unsupervised Paraphrasing via Deep Reinforcement Learningcited by 25
  9. 2021Factorising Meaning and Form for Intent-Preserving Paraphrasingcited by 22
  10. 2020Transformers to Learn Hierarchical Contexts in Multiparty Dialogue for Span-based Question Answeringcited by 13
  11. 2021Unsupervised Contextual Paraphrase Generation using Lexical Control and Reinforcement Learningcited by 10

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Citing papers per year: 2022: 5; 2023: 11; 2024: 10; 2025: 3; 2026: 2.

31 papers.

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  1. 2023Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defensecited by 401
  2. 2023Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustnesscited by 50
  3. 2022Measuring Reliability of Large Language Models through Semantic Consistencycited by 38
  4. 2023Predicting Question-Answering Performance of Large Language Models through Semantic Consistencycited by 28
  5. 2024Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challengescited by 18
  6. 2024Spotting AI's Touch: Identifying LLM-Paraphrased Spans in Textcited by 16
  7. 2023FACTIFY3M: A Benchmark for Multimodal Fact Verification with Explainability through 5W Question-Answeringcited by 15
  8. 2025Unveiling Attractor Cycles in Large Language Models: A Dynamical Systems View of Successive Paraphrasingcited by 14
  9. 2023Not All Metrics Are Guilty: Improving NLG Evaluation by Diversifying Referencescited by 11
  10. 2022Lexical Generalization Improves with Larger Models and Longer Trainingcited by 9
  11. 2023Explicit Syntactic Guidance for Neural Text Generationcited by 8
  12. 2024How often are errors in natural language reasoning due to paraphrastic variability?cited by 5
19 more
  1. 2023Zero-Shot Slot and Intent Detection in Low-Resource Languagescited by 4
  2. 2023Paraphrase Types for Generation and Detectioncited by 4
  3. 2024SaGE: Evaluating Moral Consistency in Large Language Modelscited by 3
  4. 2024Seed-Free Synthetic Data Generation Framework for Instruction-Tuning LLMs: A Case Study in Thaicited by 3
  5. 2022DATScore: Evaluating Translation with Data Augmented Translationscited by 2
  6. 2023More Robust Schema-Guided Dialogue State Tracking via Tree-Based Paraphrase Rankingcited by 2
  7. 2024HU at SemEval-2024 Task 8A: Can Contrastive Learning Learn Embeddings to Detect Machine-Generated Text?cited by 2
  8. 2023A Quality-based Syntactic Template Retriever for Syntactically-controlled Paraphrase Generationcited by 1
  9. 2024Linguistically-Controlled Paraphrase Generationcited by 1
  10. 2022Neural Embeddings for Textcited by 0
  11. 2022SimpleStyle: An Adaptable Style Transfer Approachcited by 0
  12. 2023A Benchmark for Text Expansion: Datasets, Metrics, and Baselinescited by 0
  13. 2024Action Controlled Paraphrasingcited by 0
  14. 2024Human Speech Perception in Noise: Can Large Language Models Paraphrase to Improve It?cited by 0
  15. 2024LingGen: Scalable Multi-Attribute Linguistic Control via Power-Law Maskingcited by 0
  16. 2025SMCLM: Semantically Meaningful Causal Language Modeling for Autoregressive Paraphrase Generationcited by 0
  17. 2025Copyright Detection in Large Language Models: An Ethical Approach to Generative AI Developmentcited by 0
  18. 2026ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangementcited by 0
  19. 2026Concealing LLM-Based Multi-Agent Topology via Phantom Structure Injectioncited by 0