Overcoming language priors via shuffling language bias for robust visual question answering

J Zhao, Z Yu, X Zhang, Y Yang - IEEE Access, 2023 - ieeexplore.ieee.org
Recent research has revealed the notorious language prior problem in visual question
answering (VQA) tasks based on visual-textual interaction, which indicates that well …

Overcoming language priors for visual question answering via loss rebalancing label and global context

R Cao, Z Li - Uncertainty in Artificial Intelligence, 2023 - proceedings.mlr.press
Despite the advances in Visual Question Answering (VQA), many VQA models currently
suffer from language priors (ie generating answers directly from questions without using …

A language prior based focal loss for visual question answering

M Lao, Y Guo, Y Liu, MS Lew - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
According to current research, one of the major challenges in Visual Question Answering
(VQA) models is the overdependence on language priors (and neglect of the visual …

Vqa-bc: Robust visual question answering via bidirectional chaining

M Lao, Y Guo, W Chen, N Pu… - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Current VQA models are suffering from the problem of overdependence on language bias,
which severely reduces their robustness in real-world scenarios. In this paper, we analyze …

Overcoming language priors with self-supervised learning for visual question answering

X Zhu, Z Mao, C Liu, P Zhang, B Wang… - arXiv preprint arXiv …, 2020 - arxiv.org
Most Visual Question Answering (VQA) models suffer from the language prior problem,
which is caused by inherent data biases. Specifically, VQA models tend to answer questions …

Suppressing biased samples for robust VQA

N Ouyang, Q Huang, P Li, Y Cai, B Liu… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Most existing visual question answering (VQA) models strongly rely on language bias to
answer questions, ie, they always tend to fit question-answer pairs on the train split and …

Learning from lexical perturbations for consistent visual question answering

S Whitehead, H Wu, YR Fung, H Ji, R Feris… - arXiv preprint arXiv …, 2020 - arxiv.org
Existing Visual Question Answering (VQA) models are often fragile and sensitive to input
variations. In this paper, we propose a novel approach to address this issue based on …

Fair Attention Network for Robust Visual Question Answering

Y Bi, H Jiang, Y Hu, Y Sun, B Yin - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As a prevailing cross-modal reasoning task, Visual Question Answering (VQA) has achieved
impressive progress in the last few years, where the language bias is widely studied to learn …

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

A Vosoughi, S Deng, S Zhang, Y Tian… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
To increase the generalization capability of VQA systems, many recent studies have tried to
de-bias spurious language or vision associations that shortcut the question or image to the …

Counterfactual samples synthesizing for robust visual question answering

L Chen, X Yan, J Xiao, H Zhang… - Proceedings of the …, 2020 - openaccess.thecvf.com
Abstract Despite Visual Question Answering (VQA) has realized impressive progress over
the last few years, today's VQA models tend to capture superficial linguistic correlations in …