{"total":44,"rows":[{"id":"2105.03075","title":"A Survey of Data Augmentation Approaches for NLP","created":"2021-05-07","cited_by_count":409,"area":null},{"id":"2305.11391","title":"A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation","created":"2023-05-19","cited_by_count":93,"area":null},{"id":"2310.14542","title":"Evaluating Large Language Models on Controlled Generation Tasks","created":"2023-10-23","cited_by_count":73,"area":null},{"id":"2107.07150","title":"Tailor: Generating and Perturbing Text with Semantic Controls","created":"2021-07-15","cited_by_count":68,"area":null},{"id":"2101.10579","title":"Generating Syntactically Controlled Paraphrases without Using Annotated Parallel Pairs","created":"2021-01-26","cited_by_count":45,"area":null},{"id":"2310.05280","title":"Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systems","created":"2023-10-08","cited_by_count":37,"area":null},{"id":"2202.08479","title":"On the Evaluation Metrics for Paraphrase Generation","created":"2022-02-17","cited_by_count":32,"area":null},{"id":"2305.16635","title":"Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing","created":"2023-05-26","cited_by_count":31,"area":null},{"id":"2104.05115","title":"Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models","created":"2021-04-11","cited_by_count":22,"area":null},{"id":"2105.15053","title":"Factorising Meaning and Form for Intent-Preserving Paraphrasing","created":"2021-05-31","cited_by_count":22,"area":null},{"id":"2203.03463","title":"Hierarchical Sketch Induction for Paraphrase Generation","created":"2022-03-07","cited_by_count":22,"area":null},{"id":"2405.15604","title":"Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges","created":"2024-05-24","cited_by_count":18,"area":null},{"id":"2206.12131","title":"MVP: Multi-task Supervised Pre-training for Natural Language Generation","created":"2022-06-24","cited_by_count":16,"area":null},{"id":"2105.15171","title":"Learning from Perturbations: Diverse and Informative Dialogue Generation with Inverse Adversarial Training","created":"2021-05-31","cited_by_count":13,"area":null},{"id":"2305.16585","title":"ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation","created":"2023-05-26","cited_by_count":11,"area":null},{"id":"2305.16663","title":"GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks","created":"2023-05-26","cited_by_count":10,"area":null},{"id":"2403.16038","title":"Monotonic Paraphrasing Improves Generalization of Language Model Prompting","created":"2024-03-24","cited_by_count":10,"area":null},{"id":"2106.11791","title":"Exemplars-guided Empathetic Response Generation Controlled by the Elements of Human Communication","created":"2021-06-22","cited_by_count":9,"area":null},{"id":"2506.12181","title":"Generative or Discriminative? Revisiting Text Classification in the Era of Transformers","created":"2025-06-13","cited_by_count":9,"area":null},{"id":"2306.11485","title":"Explicit Syntactic Guidance for Neural Text Generation","created":"2023-06-20","cited_by_count":8,"area":null},{"id":"2109.01484","title":"Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation","created":"2021-09-03","cited_by_count":6,"area":null},{"id":"2203.13491","title":"Striking a Balance: Alleviating Inconsistency in Pre-trained Models for Symmetric Classification Tasks","created":"2022-03-25","cited_by_count":6,"area":null},{"id":"2205.12213","title":"Principled Paraphrase Generation with Parallel Corpora","created":"2022-05-24","cited_by_count":5,"area":null},{"id":"2305.11862","title":"Reducing Sequence Length by Predicting Edit Operations with Large Language Models","created":"2023-05-19","cited_by_count":5,"area":null},{"id":"2211.00881","title":"Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations","created":"2022-11-02","cited_by_count":4,"area":null},{"id":"2305.16701","title":"PIP: Parse-Instructed Prefix for Syntactically Controlled Paraphrase Generation","created":"2023-05-26","cited_by_count":4,"area":null},{"id":"2310.07155","title":"\"A Tale of Two Movements\": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction","created":"2023-10-11","cited_by_count":4,"area":null},{"id":"2406.14164","title":"A Data-Driven Guided Decoding Mechanism for Diagnostic Captioning","created":"2024-06-20","cited_by_count":4,"area":null},{"id":"2212.13005","title":"TextBox 2.0: A Text Generation Library with Pre-trained Language Models","created":"2022-12-26","cited_by_count":3,"area":null},{"id":"2305.09598","title":"Boosting Event Extraction with Denoised Structure-to-Text Augmentation","created":"2023-05-16","cited_by_count":3,"area":null},{"id":"2309.12551","title":"Is it Possible to Modify Text to a Target Readability Level? An Initial Investigation Using Zero-Shot Large Language Models","created":"2023-09-22","cited_by_count":3,"area":null},{"id":"2105.03641","title":"Diversifying Neural Text Generation with Part-of-Speech Guided Softmax and Sampling","created":"2021-05-08","cited_by_count":2,"area":null},{"id":"2412.17111","title":"Learning to Adapt to Low-Resource Paraphrase Generation","created":"2024-12-22","cited_by_count":2,"area":null},{"id":"2301.02275","title":"Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generation","created":"2023-01-05","cited_by_count":1,"area":null},{"id":"2310.13262","title":"A Quality-based Syntactic Template Retriever for Syntactically-controlled Paraphrase Generation","created":"2023-10-20","cited_by_count":1,"area":null},{"id":"2403.17564","title":"Task-Oriented Paraphrase Analytics","created":"2024-03-26","cited_by_count":1,"area":null},{"id":"2411.01483","title":"Teaching Models to Improve on Tape","created":"2024-11-03","cited_by_count":1,"area":null},{"id":"2505.12821","title":"SynDec: A Synthesize-then-Decode Approach for Arbitrary Textual Style Transfer via Large Language Models","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2511.10441","title":"Analogical Structure, Minimal Contextual Cues and Contrastive Distractors: Input Design for Sample-Efficient Linguistic Rule Induction","created":"2025-11-13","cited_by_count":1,"area":null},{"id":"2212.03297","title":"Fine-Grained Emotional Paraphrasing along Emotion Gradients","created":"2022-10-30","cited_by_count":0,"area":null},{"id":"2405.11277","title":"Action Controlled Paraphrasing","created":"2024-05-18","cited_by_count":0,"area":null},{"id":"2510.06383","title":"Protecting De-identified Documents from Search-based Linkage Attacks","created":"2025-10-07","cited_by_count":0,"area":null},{"id":"2601.05624","title":"Text Detoxification in isiXhosa and Yor\\`ub\\'a: A Cross-Lingual Machine Learning Approach for Low-Resource African Languages","created":"2026-01-09","cited_by_count":0,"area":null},{"id":"2602.20966","title":"Blackbird Language Matrices: A Framework to Investigate the Linguistic Competence of Language Models","created":"2026-02-24","cited_by_count":0,"area":null}],"next_cursor":null}