Datasets › NeuralNews
NeuralNews
NeuralNews is a dataset for machine-generated news detection. It consists of human-generated and machine-generated articles. The human-generated articles are extracted from the GoodNews dataset, which is extracted from the New York Times. It contains 4 types of articles:
- Real Articles and Real Captions
- Real Articles and Generated Captions
- Generated Articles and Real Captions
- Generated Articles and Generated Captions
In total, it contains about 32K samples of each article type (resulting in about 128K total).
Source: Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 4 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
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Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- NeuralNews
1 variant name, as the archive lists them.
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