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Adversarial Regularization for Visual Question Answering: Strengths,
  Shortcomings, and Side Effects

Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects

20 June 2019
Gabriel Grand
Yonatan Belinkov
ArXivPDFHTML

Papers citing "Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects"

13 / 13 papers shown
Title
Towards Robust Visual Question Answering: Making the Most of Biased
  Samples via Contrastive Learning
Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning
Q. Si
Yuanxin Liu
Fandong Meng
Zheng Lin
Peng Fu
Yanan Cao
Weiping Wang
Jie Zhou
32
23
0
10 Oct 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
Robik Shrestha
Kushal Kafle
Christopher Kanan
CML
21
13
0
05 Apr 2022
A Closer Look at Debiased Temporal Sentence Grounding in Videos:
  Dataset, Metric, and Approach
A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach
Xiaohan Lan
Yitian Yuan
Xin Eric Wang
Long Chen
Zhi Wang
Lin Ma
Wenwu Zhu
CML
13
15
0
10 Mar 2022
Language bias in Visual Question Answering: A Survey and Taxonomy
Language bias in Visual Question Answering: A Survey and Taxonomy
Desen Yuan
16
12
0
16 Nov 2021
Towards Debiasing Temporal Sentence Grounding in Video
Towards Debiasing Temporal Sentence Grounding in Video
Hao Zhang
Aixin Sun
Wei Jing
Joey Tianyi Zhou
48
16
0
08 Nov 2021
Discovering the Unknown Knowns: Turning Implicit Knowledge in the
  Dataset into Explicit Training Examples for Visual Question Answering
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering
Jihyung Kil
Cheng Zhang
D. Xuan
Wei-Lun Chao
53
20
0
13 Sep 2021
End-to-End Self-Debiasing Framework for Robust NLU Training
End-to-End Self-Debiasing Framework for Robust NLU Training
Abbas Ghaddar
Philippe Langlais
Mehdi Rezagholizadeh
Ahmad Rashid
UQCV
10
36
0
05 Sep 2021
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing
  Functional Entropies
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies
Itai Gat
Idan Schwartz
A. Schwing
Tamir Hazan
51
89
0
21 Oct 2020
Counterfactual Variable Control for Robust and Interpretable Question
  Answering
Counterfactual Variable Control for Robust and Interpretable Question Answering
S. Yu
Yulei Niu
Shuohang Wang
Jing Jiang
Qianru Sun
AAML
OOD
34
9
0
12 Oct 2020
Fine-Grained Grounding for Multimodal Speech Recognition
Fine-Grained Grounding for Multimodal Speech Recognition
Tejas Srinivasan
Ramon Sanabria
Florian Metze
Desmond Elliott
19
11
0
05 Oct 2020
On Adversarial Removal of Hypothesis-only Bias in Natural Language
  Inference
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
AAML
29
69
0
09 Jul 2019
Don't Take the Premise for Granted: Mitigating Artifacts in Natural
  Language Inference
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
19
94
0
09 Jul 2019
Hypothesis Only Baselines in Natural Language Inference
Hypothesis Only Baselines in Natural Language Inference
Adam Poliak
Jason Naradowsky
Aparajita Haldar
Rachel Rudinger
Benjamin Van Durme
187
576
0
02 May 2018
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