mlsanityData to 13 Oct 2026

On Unifying Misinformation Detection

arXiv 2104.05243 ↗First posted 12 Apr 2021cs.AI cs.CLcited by 10

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Abstract (arXiv)

In this paper, we introduce UnifiedM2, a general-purpose misinformation model that jointly models multiple domains of misinformation with a single, unified setup. The model is trained to handle four tasks: detecting news bias, clickbait, fake news, and verifying rumors. By grouping these tasks together, UnifiedM2learns a richer representation of misinformation, which leads to state-of-the-art or comparable performance across all tasks. Furthermore, we demonstrate that UnifiedM2's learned representation is helpful for few-shot learning of unseen misinformation tasks/datasets and model's generalizability to unseen events.

Key facts. Cited by 10 papers in the map (data through 13 Oct 2026). Builds on 20 of its 38 references that are in the map. First posted on arXiv 12 Apr 2021.

Builds on

20 of 38 references.

References · 20

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8 more
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Cited by year

Citing papers per year: 2021: 2; 2022: 2; 2023: 2; 2024: 4.

10 papers.