Article

Improving Users' Mental Model with Attention-directed Counterfactual Edits

2021-06-25

Abstract excerpt

In the domain of Visual Question Answering (VQA), studies have shown improvement in users’ mental model of the VQA system when they are exposed to examples of how these systems answer certain Image-Question (IQ) pairs. In this work, we show that showing controlled counterfactual image-question examples are more effective at improving the mental model of users as compared to simply showing random examples. We compa...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 3363bf4d-0e28-595c-aad6-a19fdb01ec3e
DOI: 10.22541/au.162464875.59047443/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Improving Users' Mental Model with Attention-directed Counterfactual EditsDOI 10.22541/au.162464875.59047443/v1Read

Ask Twice, Look Twice: Training-Free Consistency Filtering for Reliable Medical VQASemantic proximity Read

Towards Multimodal Retrieval-Augmented Generation for Medical Visual Question AnsweringSemantic proximity Read

Generative AI for Text-to-Video Generation: Recent Advances and Future DirectionsSemantic proximity Read

Goal-Driven Visual Question Generation from Radiology ImagesSemantic proximity Read

RobustVLM: Enhancing Large Vision-Language Models through Adaptive Visual Context Learning, Weak-to-Strong Robust Transfer, and Domain-Adaptive FeedbackSemantic proximity Read

Evaluating Text-to-Image Generated Photorealistic Images of Human AnatomySemantic proximity Read

Enhancing Human Detection of Real and AI-Generated Hyperrealistic FacesSemantic proximity Read

Enhancing Human Detection of Real and AI-Generated Hyperrealistic FacesSemantic proximity Read

Differentiable Retrieval-Guided Multimodal Reasoning for Knowledge-Intensive Visual Question UnderstandingSemantic proximity Read

Enhancing Caption Fidelity via Explanation-Guided Captioning with Vision-Language Fine-TuningSemantic proximity Read

An Efficient and Training-Free Approach for Subject-Driven Text-to-Image GenerationSemantic proximity Read

Medical Image Captioning via Generative Pretrained TransformersSemantic proximity Read