Deception Detection
11 papers with code • 0 benchmarks • 2 datasets
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Libraries
Use these libraries to find Deception Detection models and implementationsMost 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.
Literature Meets Data: A Synergistic Approach to Hypothesis Generation
Additionally, we conduct the first human evaluation to assess the utility of LLM-generated hypotheses in assisting human decision-making on two challenging tasks: deception detection and AI generated content 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.
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning
Despite this, deception detection research is hindered by the lack of high-quality deception datasets, as well as the difficulties of learning multimodal features effectively.
UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection
Verbal deception has been studied in psychology, forensics, and computational linguistics for a variety of reasons, like understanding behaviour patterns, identifying false testimonies, and detecting deception in online communication.
Spatiotemporal Pyramidal CNN with Depth-Wise Separable Convolution for Eye Blinking Detection in the Wild
Eye blinking detection in the wild plays an essential role in deception detection, driving fatigue detection, etc.
MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews
Using this dataset, we conduct extensive linguistic analyses to (1) compare the AI fake hotel reviews to real hotel reviews, and (2) identify the factors that influence the deception detection model performance.