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Found 5 papers, 2 papers with code
Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation
We propose an uncertainty quantification framework that leverages both direct confidence elicitation and sampled-based consistency methods to provide better calibration for NLP misinformation mitigation solutions.
Uncertainty Resolution in Misinformation Detection
Misinformation poses a variety of risks, such as undermining public trust and distorting factual discourse.
Party Prediction for Twitter
A large number of studies on social media compare the behaviour of users from different political parties.
Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4
We propose focusing on generalization, uncertainty, and how to leverage recent large language models, in order to create more practical tools to evaluate information veracity in contexts where perfect classification is impossible.
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