23 citations · 43 across the 3 of their papers we have counts for
7 papers
The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims
Li Shi, Nilavra Bhattacharya, Anubrata Das +2
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…
Vision Skills Needed to Answer Visual Questions
Xiaoyu Zeng, Yanan Wang, Tai-Yin Chiu +2
The task of answering questions about images has garnered attention as a practical service for assisting populations with visual impairments as well as a visual Turing test for the…
Captioning Images Taken by People Who Are Blind
Danna Gurari, Yinan Zhao, Meng Zhang +1
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…
Relevance Prediction from Eye-movements Using Semi-interpretable Convolutional Neural Networks
Nilavra Bhattacharya, Somnath Rakshit, Jacek Gwizdka +1
We propose an image-classification method to predict the perceived-relevance of text documents from eye-movements. An eye-tracking study was conducted where participants read short…
VizWiz Dataset Browser: A Tool for Visualizing Machine Learning Datasets
Nilavra Bhattacharya, Danna Gurari
We present a visualization tool to exhaustively search and browse through a set of large-scale machine learning datasets. Built on the top of the VizWiz dataset, our dataset browse…
Why Does a Visual Question Have Different Answers?
Nilavra Bhattacharya, Qing Li, Danna Gurari
Visual question answering is the task of returning the answer to a question about an image. A challenge is that different people often provide different answers to the same visual…