Deception Detection

11 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

Literature Meets Data: A Synergistic Approach to Hypothesis Generation

chicagohai/hypothesis-generation 22 Oct 2024

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.

The Mafiascum Dataset: A Large Text Corpus for Deception Detection

bopjesvla/thesis 19 Nov 2018

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

siddhu001/evaluating-explanations 17 Dec 2021

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

MahatKC/CanLiesBeFaked 23 Nov 2022

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

nms05/audio-visual-deception-detection-dolos-dataset-and-parameter-efficient-crossmodal-learning ICCV 2023

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

aswathyve/unifieddeceptioncorpus 5 Jun 2023

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

bachzz/dws-pbbn 20 Jun 2023

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

michigannlp/multilingual_reviews_deception 19 Apr 2024

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.