23 citations · 23 across the 1 of their papers we have counts for
4 papers
The Impact of Explanations on AI Competency Prediction in VQA
Kamran Alipour, Arijit Ray, Xiao Lin +3
Explainability is one of the key elements for building trust in AI systems. Among numerous attempts to make AI explainable, quantifying the effect of explanations remains a challen…
Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation
Arijit Ray, Karan Sikka, Ajay Divakaran +2
While models for Visual Question Answering (VQA) have steadily improved over the years, interacting with one quickly reveals that these models lack consistency. For instance, if a…
Can You Explain That? Lucid Explanations Help Human-AI Collaborative Image Retrieval
Arijit Ray, Yi Yao, Rakesh Kumar +2
While there have been many proposals on making AI algorithms explainable, few have attempted to evaluate the impact of AI-generated explanations on human performance in conducting…
Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention
Shalini Ghosh, Giedrius Burachas, Arijit Ray +1
In this paper, we present a novel approach for the task of eXplainable Question Answering (XQA), i.e., generating natural language (NL) explanations for the Visual Question Answeri…