Model: feradauto/scibert_nlp4sg
Author: feradauto
Pipeline: text-classification
Library: transformers
Tags: transformers, pytorch, bert, text-classification, en, arxiv:2305.05471, license:apache-2.0, endpoints_compatible, region:us
Card metadata: license: apache-2.0
language: en
metrics: accuracy
pipeline_tag: text-classification
widget: text: On Unifying Misinformation Detection. 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, UNIFIEDM2 learns a richer representation of misinformation, which leads to stateof-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.
example_title: Misinformation Detection
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Created: 2023-05-03 06:00:41