B

Bart CaPE Xsum

Developed by praf-choub
CaPE is a contrastive parameter ensemble method designed to reduce hallucination in abstractive summarization.
Downloads 22
Release Time : 4/23/2022

Model Overview

CaPE employs contrastive parameter integration techniques to mitigate hallucination issues during abstractive summarization, enhancing the accuracy and reliability of summaries.

Model Features

Reducing Hallucination
Effectively reduces hallucination in abstractive summarization through contrastive parameter integration techniques.
Improving Accuracy
Generates more accurate and reliable summaries.

Model Capabilities

Abstractive Summarization
Reducing Hallucination in Summaries

Use Cases

Text Summarization
News Summarization
Generates concise summaries of news articles while minimizing hallucinated content.
Enhances the accuracy and reliability of summaries.
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