Cross Modality Bias in Visual Question Answering: A Causal View With Possible Worlds VQA-Reference-Cited by-同舟云学术

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Cross Modality Bias in Visual Question Answering: A Causal View With Possible Worlds VQA

Published:2024 Issue: Volume:26 Page:8609-8624
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Vosoughi Ali¹^ORCID,Deng Shijian²^ORCID,Zhang Songyang³^ORCID,Tian Yapeng²^ORCID,Xu Chenliang³^ORCID,Luo Jiebo³^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA

2. Department of Computer Science, University of Texas Dallas, Dallas, TX, USA

3. Department of Computer Science, University of Rochester, Rochester, NY, USA

Funder

National Science Foundation

National Nuclear Security Administration

NIH

Defense Advanced Research Projects Agency

Center of Excellence in Data Science

Cisco

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/6046/10384483/10477535-aam.pdf

Reference69 articles.

1. Introspective distillation for robust question answering;Niu,2021

2. RUBi: Reducing unimodal biases for visual question answering;Cadene,2019

3. MUREL: Multimodal Relational Reasoning for Visual Question Answering

4. Overcoming Language Priors in VQA via Decomposed Linguistic Representations

5. Overcoming language priors in visual question answering with adversarial regularization;Ramakrishnan,2018

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