3260 papers • 126 benchmarks • 313 datasets
Generation of larger segments of text with consistent topic and evolving story.
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These leaderboards are used to track progress in news-generation-8
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Use these libraries to find news-generation-8 models and implementations
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The development of a corpus of Finnish ice hockey news, edited to be suitable for training of end-to-end news generation methods, is reported on and generation of text is demonstrated, which was judged by journalists to be relatively close to a viable product.
The details of the pipeline and the techniques used for full generation of fake news, from dataset collection to presentation as a media art project on the internet are shared.
A novel generation method FACTGEN is developed to generate high-quality news content that retrieves external facts to enrich the output and reconstructs the input claim from the generated content to improve the consistency among the input and the output.
The first advanced Arabic language generation model, AraGPT2, trained from scratch on a large Arabic corpus of internet text and news articles is developed and an automatic discriminator model with a 98% percent accuracy in detecting model-generated text is released.
Adding a benchmark result helps the community track progress.