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Don't Just Assume; Look and Answer: Overcoming Priors for Visual
  Question Answering

Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering

1 December 2017
Aishwarya Agrawal
Dhruv Batra
Devi Parikh
Aniruddha Kembhavi
    OOD
ArXivPDFHTML

Papers citing "Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering"

50 / 330 papers shown
Title
Mitigating Gender Bias in Captioning Systems
Mitigating Gender Bias in Captioning Systems
Ruixiang Tang
Mengnan Du
Yuening Li
Zirui Liu
Na Zou
Xia Hu
FaML
11
65
0
15 Jun 2020
Estimating semantic structure for the VQA answer space
Estimating semantic structure for the VQA answer space
Corentin Kervadec
G. Antipov
M. Baccouche
Christian Wolf
18
4
0
10 Jun 2020
Roses Are Red, Violets Are Blue... but Should Vqa Expect Them To?
Roses Are Red, Violets Are Blue... but Should Vqa Expect Them To?
Corentin Kervadec
G. Antipov
M. Baccouche
Christian Wolf
OOD
8
86
0
09 Jun 2020
Counterfactual VQA: A Cause-Effect Look at Language Bias
Counterfactual VQA: A Cause-Effect Look at Language Bias
Yulei Niu
Kaihua Tang
Hanwang Zhang
Zhiwu Lu
Xiansheng Hua
Ji-Rong Wen
CML
19
392
0
08 Jun 2020
On the Value of Out-of-Distribution Testing: An Example of Goodhart's
  Law
On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law
Damien Teney
Kushal Kafle
Robik Shrestha
Ehsan Abbasnejad
Christopher Kanan
A. Hengel
OODD
OOD
11
145
0
19 May 2020
Does Data Augmentation Improve Generalization in NLP?
Does Data Augmentation Improve Generalization in NLP?
Rohan Jha
Charles Lovering
Ellie Pavlick
9
10
0
30 Apr 2020
Look at the First Sentence: Position Bias in Question Answering
Look at the First Sentence: Position Bias in Question Answering
Miyoung Ko
Jinhyuk Lee
Hyunjae Kim
Gangwoo Kim
Jaewoo Kang
FaML
OOD
11
99
0
30 Apr 2020
Generative Data Augmentation for Commonsense Reasoning
Generative Data Augmentation for Commonsense Reasoning
Yiben Yang
Chaitanya Malaviya
Jared Fernandez
Swabha Swayamdipta
Ronan Le Bras
Ji-ping Wang
Chandra Bhagavatula
Yejin Choi
Doug Downey
LRM
11
91
0
24 Apr 2020
Learning What Makes a Difference from Counterfactual Examples and
  Gradient Supervision
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision
Damien Teney
Ehsan Abbasnejad
A. Hengel
OOD
SSL
CML
15
116
0
20 Apr 2020
Avoiding the Hypothesis-Only Bias in Natural Language Inference via
  Ensemble Adversarial Training
Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training
Joe Stacey
Pasquale Minervini
Haim Dubossarsky
Sebastian Riedel
Tim Rocktaschel
AI4CE
12
8
0
16 Apr 2020
Visual Grounding Methods for VQA are Working for the Wrong Reasons!
Visual Grounding Methods for VQA are Working for the Wrong Reasons!
Robik Shrestha
Kushal Kafle
Christopher Kanan
CML
6
35
0
12 Apr 2020
An Entropy Clustering Approach for Assessing Visual Question Difficulty
An Entropy Clustering Approach for Assessing Visual Question Difficulty
K. Terao
Toru Tamaki
B. Raytchev
K. Kaneda
Shuníchi Satoh
OOD
AAML
18
1
0
12 Apr 2020
P $\approx$ NP, at least in Visual Question Answering
P ≈\approx≈ NP, at least in Visual Question Answering
Shailza Jolly
Sebastián M. Palacio
Joachim Folz
Federico Raue
Jörn Hees
Andreas Dengel
11
0
0
26 Mar 2020
Linguistically Driven Graph Capsule Network for Visual Question
  Reasoning
Linguistically Driven Graph Capsule Network for Visual Question Reasoning
Qingxing Cao
Xiaodan Liang
Keze Wang
Liang Lin
GNN
11
3
0
23 Mar 2020
Invariant Rationalization
Invariant Rationalization
Shiyu Chang
Yang Zhang
Mo Yu
Tommi Jaakkola
179
201
0
22 Mar 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI
L. Arras
Ahmed Osman
Wojciech Samek
XAI
AAML
16
146
0
16 Mar 2020
Counterfactual Samples Synthesizing for Robust Visual Question Answering
Counterfactual Samples Synthesizing for Robust Visual Question Answering
Long Chen
Xin Yan
Jun Xiao
Hanwang Zhang
Shiliang Pu
Yueting Zhuang
OOD
AAML
142
290
0
14 Mar 2020
Deconfounded Image Captioning: A Causal Retrospect
Deconfounded Image Captioning: A Causal Retrospect
Xu Yang
Hanwang Zhang
Jianfei Cai
CML
8
114
0
09 Mar 2020
Toward Interpretability of Dual-Encoder Models for Dialogue Response
  Suggestions
Toward Interpretability of Dual-Encoder Models for Dialogue Response Suggestions
Yitong Li
Dianqi Li
Sushant Prakash
Peng Wang
11
2
0
02 Mar 2020
Unbiased Scene Graph Generation from Biased Training
Unbiased Scene Graph Generation from Biased Training
Kaihua Tang
Yulei Niu
Jianqiang Huang
Jiaxin Shi
Hanwang Zhang
CML
17
668
0
27 Feb 2020
Unshuffling Data for Improved Generalization
Unshuffling Data for Improved Generalization
Damien Teney
Ehsan Abbasnejad
A. Hengel
OOD
12
75
0
27 Feb 2020
On the General Value of Evidence, and Bilingual Scene-Text Visual
  Question Answering
On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering
Xinyu Wang
Yuliang Liu
Chunhua Shen
Chun Chet Ng
Canjie Luo
Lianwen Jin
C. Chan
A. Hengel
Liangwei Wang
15
90
0
24 Feb 2020
Accuracy vs. Complexity: A Trade-off in Visual Question Answering Models
Accuracy vs. Complexity: A Trade-off in Visual Question Answering Models
M. Farazi
Salman H. Khan
Nick Barnes
21
18
0
20 Jan 2020
SQuINTing at VQA Models: Introspecting VQA Models with Sub-Questions
SQuINTing at VQA Models: Introspecting VQA Models with Sub-Questions
Ramprasaath R. Selvaraju
Purva Tendulkar
Devi Parikh
Eric Horvitz
Marco Tulio Ribeiro
Besmira Nushi
Ece Kamar
LRM
6
14
0
20 Jan 2020
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning
  Models
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning Models
Jiamei Sun
Sebastian Lapuschkin
Wojciech Samek
Alexander Binder
FAtt
20
29
0
04 Jan 2020
Measuring Compositional Generalization: A Comprehensive Method on
  Realistic Data
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
Daniel Keysers
Nathanael Scharli
Nathan Scales
Hylke Buisman
Daniel Furrer
...
Tibor Tihon
Dmitry Tsarkov
Xiao Wang
Marc van Zee
Olivier Bousquet
CoGe
13
346
0
20 Dec 2019
Towards Causal VQA: Revealing and Reducing Spurious Correlations by
  Invariant and Covariant Semantic Editing
Towards Causal VQA: Revealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing
Vedika Agarwal
Rakshith Shetty
Mario Fritz
CML
AAML
19
155
0
16 Dec 2019
Assessing the Robustness of Visual Question Answering Models
Assessing the Robustness of Visual Question Answering Models
Jia-Hong Huang
Modar Alfadly
Bernard Ghanem
M. Worring
AAML
OOD
15
23
0
30 Nov 2019
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning
  Baselines
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines
Jingxiang Lin
Unnat Jain
A. Schwing
LRM
ReLM
26
9
0
31 Oct 2019
Multi-modal Deep Analysis for Multimedia
Multi-modal Deep Analysis for Multimedia
Wenwu Zhu
Xin Eric Wang
Hongzhi Li
19
38
0
11 Oct 2019
Learning De-biased Representations with Biased Representations
Learning De-biased Representations with Biased Representations
Hyojin Bahng
Sanghyuk Chun
Sangdoo Yun
Jaegul Choo
Seong Joon Oh
OOD
293
274
0
07 Oct 2019
On Incorporating Semantic Prior Knowledge in Deep Learning Through
  Embedding-Space Constraints
On Incorporating Semantic Prior Knowledge in Deep Learning Through Embedding-Space Constraints
Damien Teney
Ehsan Abbasnejad
A. Hengel
NAI
16
9
0
30 Sep 2019
Compact Trilinear Interaction for Visual Question Answering
Compact Trilinear Interaction for Visual Question Answering
Tuong Khanh Long Do
Thanh-Toan Do
Huy Tran
Erman Tjiputra
Quang-Dieu Tran
26
59
0
26 Sep 2019
Unified Vision-Language Pre-Training for Image Captioning and VQA
Unified Vision-Language Pre-Training for Image Captioning and VQA
Luowei Zhou
Hamid Palangi
Lei Zhang
Houdong Hu
Jason J. Corso
Jianfeng Gao
MLLM
VLM
250
926
0
24 Sep 2019
Non-monotonic Logical Reasoning Guiding Deep Learning for Explainable
  Visual Question Answering
Non-monotonic Logical Reasoning Guiding Deep Learning for Explainable Visual Question Answering
Heather Riley
Mohan Sridharan
NAI
11
0
0
23 Sep 2019
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known
  Dataset Biases
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases
Christopher Clark
Mark Yatskar
Luke Zettlemoyer
OOD
15
458
0
09 Sep 2019
Learning Credible Deep Neural Networks with Rationale Regularization
Learning Credible Deep Neural Networks with Rationale Regularization
Mengnan Du
Ninghao Liu
Fan Yang
Xia Hu
FaML
10
45
0
13 Aug 2019
SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial
  Relation Recognition
SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition
Kaiyu Yang
Olga Russakovsky
Jia Deng
3DPC
22
58
0
07 Aug 2019
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for
  Vision-and-Language Tasks
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Jiasen Lu
Dhruv Batra
Devi Parikh
Stefan Lee
SSL
VLM
8
3,610
0
06 Aug 2019
Answering Questions about Data Visualizations using Efficient Bimodal
  Fusion
Answering Questions about Data Visualizations using Efficient Bimodal Fusion
Kushal Kafle
Robik Shrestha
Brian L. Price
Scott D. Cohen
Christopher Kanan
6
58
0
05 Aug 2019
V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive
  Matrices
V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices
Damien Teney
Peng Wang
Jiewei Cao
Lingqiao Liu
Chunhua Shen
A. Hengel
7
30
0
29 Jul 2019
Bilinear Graph Networks for Visual Question Answering
Bilinear Graph Networks for Visual Question Answering
Dalu Guo
Chang Xu
Dacheng Tao
GNN
27
50
0
23 Jul 2019
Trends in Integration of Vision and Language Research: A Survey of
  Tasks, Datasets, and Methods
Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
Aditya Mogadala
M. Kalimuthu
Dietrich Klakow
VLM
15
132
0
22 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
Learning by Abstraction: The Neural State Machine
Learning by Abstraction: The Neural State Machine
Drew A. Hudson
Christopher D. Manning
NAI
OCL
8
258
0
09 Jul 2019
ICDAR 2019 Competition on Scene Text Visual Question Answering
ICDAR 2019 Competition on Scene Text Visual Question Answering
Ali Furkan Biten
Rubèn Pérez Tito
Andrés Mafla
Lluís Gómez
Marçal Rusiñol
Minesh Mathew
C. V. Jawahar
Ernest Valveny
Dimosthenis Karatzas
6
74
0
30 Jun 2019
RUBi: Reducing Unimodal Biases in Visual Question Answering
RUBi: Reducing Unimodal Biases in Visual Question Answering
Rémi Cadène
Corentin Dancette
H. Ben-younes
Matthieu Cord
Devi Parikh
CML
8
365
0
24 Jun 2019
Investigating Biases in Textual Entailment Datasets
Investigating Biases in Textual Entailment Datasets
Shawn Tan
Yikang Shen
Chin-Wei Huang
Aaron Courville
14
8
0
23 Jun 2019
Adversarial Regularization for Visual Question Answering: Strengths,
  Shortcomings, and Side Effects
Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects
Gabriel Grand
Yonatan Belinkov
8
67
0
20 Jun 2019
Scene Text Visual Question Answering
Scene Text Visual Question Answering
Ali Furkan Biten
Rubèn Pérez Tito
Andrés Mafla
Lluís Gómez
Marçal Rusiñol
Ernest Valveny
C. V. Jawahar
Dimosthenis Karatzas
8
342
0
31 May 2019
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