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

Quality Controlled Paraphrase Generation (ACL 2022)

Data Augmentation by Backtranslation (DAB) ヽ( •_-)ᕗ

NAACL 2019: Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation

VietQuill is a unified framework for Vietnamese paraphrase generation, evaluation, and quality control, supporting both research and production applications. We are committed to advancing Vietnamese paraphrase generation by making state-of-the-art methods accessible, customizable, and easy to integrate into real-world workflows.

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

Code for our EACL-2021 paper "Generating Syntactically Controlled Paraphrases without Using Annotated Parallel Pairs".

Create paraphrasing korean sentence with GPT-3

This repository contains the data and code for the paper "Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors" (SPNLP@ACL2022)

Code for paper Document-Level Paraphrase Generation with Sentence Rewriting and Reordering by Zhe Lin, Yitao Cai and Xiaojun Wan. This paper is accepted by Findings of EMNLP'21.

A sentence paraphraser based on dependency parsing and word embedding similarity.