5 papers with code • 0 benchmarks • 2 datasets
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Most implemented papers
"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection
In this paper, we present liar: a new, publicly available dataset for fake news detection.
``Liar, Liar Pants on Fire'': A New Benchmark Dataset for Fake News Detection
In this paper, we present LIAR: a new, publicly available dataset for fake news detection.
The Mafiascum Dataset: A Large Text Corpus for Deception Detection
Detecting deception in natural language has a wide variety of applications, but because of its hidden nature there are currently no public, large-scale sources of labeled deceptive text.
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations
Through our evaluation, we observe that for a linear bag-of-words model, participants with access to the feature coefficients during training are able to cause a larger reduction in model confidence in the testing phase when compared to the no-explanation control.
Can lies be faked? Comparing low-stakes and high-stakes deception video datasets from a Machine Learning perspective
Despite the great impact of lies in human societies and a meager 54% human accuracy for Deception Detection (DD), Machine Learning systems that perform automated DD are still not viable for proper application in real-life settings due to data scarcity.