[ACL-IJCNLP 2021] Self-Supervised Multimodal Opinion Summarization
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Updated
Apr 6, 2024 - Python
[ACL-IJCNLP 2021] Self-Supervised Multimodal Opinion Summarization
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021.
Abstractive Text Summarization with T5, assessed using the ROUGE metrics 🌟📊
Transforming lengthy textual content into concise and meaningful summaries is the essence of this project. Leveraging the power of the Pegasus model, our abstractive text summarization repository aims to distill complex information into succinct and coherent summaries. Pegasus, state-of-the-art pre-trained model, excel in generating human like text
Abstractive text summarisation using BART model on articles data.
Abstractive Text Summarization using Transformer
News Headline and Summary Generation through Abstractive Summarization: Project Repo for Adavanced Machine Learning (AML) course at Ashoka
Speaker Diarization + Speech to text + abstract summerization
Summarizing text to extract key ideas and arguments
ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation
Abstractive text summarization generates a shorter version of a given sentence while attempting to preserve its contextual meaning. In our approach we model the problem using an attentional encoder decoder which ensures that the decoder focuses on the appropriate input words at each step of our generation.
Abstractive summarisation using Bert as encoder and Transformer Decoder
Using various NLP libraries for Text Summarization
Extractive and Abstractive Text Summarization of US Supreme Court Opinions
Using a deep learning model that takes advantage of LSTM and a custom Attention layer, we create an algorithm that is able to train on reviews and existent summaries to churn out and generate brand new summaries of its own.
Deep Reinforcement Learning For Sequence to Sequence Models
A curated list of resources dedicated to text summarization
Implementation of an Attention-based LSTM Encoder-Decoder Approach for Abstractive Text Summarization
An optimized Transformer based abstractive summarization model with Tensorflow
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