code for "S2TD: A Tree-Structured Decoder for Image Paragraph Captioning" accepted by MMAsia 2021
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Updated
Nov 14, 2021 - Python
code for "S2TD: A Tree-Structured Decoder for Image Paragraph Captioning" accepted by MMAsia 2021
Data and code for Kang et al., EMNLP 2019's paper titled "Linguistic Versus Latent Relations for Modeling a Flow in Paragraphs"
Generated image description in the form of coherent paragraphs using Densecap(CNN for Dense Captioning) and Hierarchical RNN and Model was able to perform as good as state-of-art in terms of metrics inclined towards human-like sentences.
A solution to find the best order of random sentences in a paragraph Using Bert algorithm and PyTorch.
MedSiML: A Multilingual Approach for Simplifying Medical Texts. This repository contains our extended medical text simplification dataset and all the models fine-tuned using it.
Text::KnuthPlass paragraph shaping package for Perl
This project is a simple React application that generates random paragraphs of text. It allows users to specify the number of paragraphs they want to generate.
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