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Found 7 papers, 2 papers with code
The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims
We conducted a lab-based eye-tracking study to investigate how the interactivity of an AI-powered fact-checking system affects user interactions, such as dwell time, attention, and mental resources involved in using the system.
Captioning Images Taken by People Who Are Blind
While an important problem in the vision community is to design algorithms that can automatically caption images, few publicly-available datasets for algorithm development directly address the interests of real users.
Relevance Prediction from Eye-movements Using Semi-interpretable Convolutional Neural Networks
The trained classifier is used to predict participants' perceived-relevance of news articles from the corresponding scanpath images.
VizWiz Dataset Browser: A Tool for Visualizing Machine Learning Datasets
We present a visualization tool to exhaustively search and browse through a set of large-scale machine learning datasets.
Why Does a Visual Question Have Different Answers?
Visual question answering is the task of returning the answer to a question about an image.
Relating Eye-Tracking Measures With Changes In Knowledge on Search Tasks
Our results show that the participants with higher change in knowledge differ significantly in terms of their total reading-sequence-length, reading-sequence-duration, and number of reading fixations, when compared to participants with lower knowledge-change.
FWLBP: A Scale Invariant Descriptor for Texture Classification
In this paper we propose a novel texture descriptor called Fractal Weighted Local Binary Pattern (FWLBP).
