Text Style Transfer

Grammarly’s Yahoo Answers Formality Corpus (GYAFC) is the largest dataset for any style containing a total of 110K informal / formal sentence pairs. Yahoo Answers is a question answering forum, contains a large number of informal sentences and allows redistribution of data. The authors used the Yahoo Answers L6 corpus to create the GYAFC dataset of informal and formal sentence pairs. In order to ensure a uniform distribution of data, they removed sentences that are questions, contain URLs, and are shorter than 5 words or longer than 25. After these preprocessing steps, 40 million sentences remain. The Yahoo Answers corpus consists of several different domains like Business, Entertainment & Music, Travel, Food, etc. Pavlick and Tetreault formality classifier (PT16) shows that the formality level varies significantly across different genres. In order to control for this variation, the authors work with two specific domains that contain the most informal sentences and show results on training and testing within those categories. The authors use the formality classifier from PT16 to identify informal sentences and train this classifier on the Answers genre of the PT16 corpus which consists of nearly 5,000 randomly selected sentences from Yahoo Answers manually annotated on a scale of -3 (very informal) to 3 (very formal). They find that the domains of Entertainment & Music and Family & Relationships contain the most informal sentences and create the GYAFC dataset using these domains. Source: Dear Sir or Madam, May I Introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer

The Yelp Dataset is a valuable resource for academic research, teaching, and learning. It provides a rich collection of real-world data related to businesses, reviews, and user interactions. Here are the key details about the Yelp Dataset: Reviews: A whopping 6,990,280 reviews from users. Businesses: Information on 150,346 businesses. Pictures: A collection of 200,100 pictures. Metropolitan Areas: Data from 11 metropolitan areas. Tips: Over 908,915 tips provided by 1,987,897 users. Business Attributes: Details like hours, parking availability, and ambiance for more than 1.2 million businesses. Aggregated Check-ins: Historical check-in data for each of the 131,930 businesses.

Touchdown is a corpus for executing navigation instructions and resolving spatial descriptions in visual real-world environments. The task is to follow instruction to a goal position and there find a hidden object, Touchdown the bear. Source: https://github.com/lil-lab/touchdown Image Source: https://github.com/lil-lab/touchdown

TextSeg is a large-scale fine-annotated and multi-purpose text detection and segmentation dataset, collecting scene and design text with six types of annotations: word- and character-wise bounding polygons, masks and transcriptions. Source: https://github.com/SHI-Labs/Rethinking-Text-Segmentation Image Source: https://github.com/SHI-Labs/Rethinking-Text-Segmentation

StylePTB is a fine-grained text style transfer benchmark. It consists of paired sentences undergoing 21 fine-grained stylistic changes spanning atomic lexical, syntactic, semantic, and thematic transfers of text, as well as compositions of multiple transfers which allow modelling of fine-grained stylistic changes as building blocks for more complex, high-level transfers.

** XFORMAL** is a multilingual formal style transfer benchmark of multiple formal reformulations of informal text in Brazilian Portuguese, French, and Italian.

We construct a style-balanced dataset, called StyleGallery, covering several open source datasets. Specifically, StyleGallery includes JourneyDB, a dataset comprising a broad spectrum of diverse styles derived from MidJourney, and WIKIART, with extensive fine-grained painting styles, such as pointillism and ink drawing, and a subset of stylized images from LAION-Aesthetics.

TextBox 2.0 is a comprehensive and unified library for text generation, focusing on the use of pre-trained language models (PLMs). The library covers 13 common text generation tasks and their corresponding 83 datasets and further incorporates 45 PLMs covering general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight PLMs. Source: TextBox 2.0: A Text Generation Library with Pre-trained Language Models Image Source: https://arxiv.org/pdf/2212.13005v1.pdf