There are 31 repositories under paraphrase-generation topic.
A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
Sentence paraphrase generation at the sentence level
Neural Paraphrase Generation
Implementation of NeurIPS 19 paper: Paraphrase Generation with Latent Bag of Words
BotSIM - a data-efficient end-to-end Bot SIMulation toolkit for evaluation, diagnosis, and improvement of commercial chatbots
Free paraphrasing tool / article rewriter
This repository contains the data and code for the paper "An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase Generation" (EMNLP2019).
TACL 2020: Syntax-Guided Controlled Generation of Paraphrases
NAACL 2019: Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation
Quality Controlled Paraphrase Generation (ACL 2022)
Implementation of NeurIPS 20 paper: Latent Template Induction with Gumbel-CRFs
Code for paper title "Learning Semantic Sentence Embeddings using Pair-wise Discriminator" COLING-2018
Paraphrase Generation model using pair-wise discriminator loss
"Unsupervised Paraphrase Generation using Pre-trained Language Model."
A sentence paraphraser based on dependency parsing and word embedding similarity.
📄Neural Sentential Paraphrase Generation to Augment Chatbot Training Dataset
Use-cases of Hugging Face's BERT (e.g. paraphrase generation, unsupervised extractive summarization).
Paraphrase Generation Using Deep Reinforcement Learning - MSc Thesis
Python project to create paraphrase of any text content
An implementation of data augmentation methods for natural language processing tasks.
This repository contains the code, data, and associated models of the paper titled "BanglaParaphrase: A High-Quality Bangla Paraphrase Dataset", accepted in Proceedings of the Asia-Pacific Chapter of the Association for Computational Linguistics: AACL 2022.
The official implementation of the EMNLP 2022 paper "How Large Language Models are Transforming Machine-Paraphrased Plagiarism".
Software implementation of research of the generation of strong paraphrases and new metrics for the validation of strong paraphrases.
Paraphrase generation with GPT-J on google colab!!
Paraphase Generation
Поэтический перефразировщик