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Improving VQA and its Explanations \\ by Comparing Competing
  Explanations

Improving VQA and its Explanations \\ by Comparing Competing Explanations

28 June 2020
Jialin Wu
Liyan Chen
Raymond J. Mooney
    FAtt
    AAML
ArXivPDFHTML

Papers citing "Improving VQA and its Explanations \\ by Comparing Competing Explanations"

5 / 5 papers shown
Title
Towards Reasoning-Aware Explainable VQA
Towards Reasoning-Aware Explainable VQA
Rakesh Vaideeswaran
Feng Gao
Abhinav Mathur
Govind Thattai
LRM
22
3
0
09 Nov 2022
CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
Leonard Salewski
A. Sophia Koepke
Hendrik P. A. Lensch
Zeynep Akata
LRM
NAI
25
20
0
05 Apr 2022
REX: Reasoning-aware and Grounded Explanation
REX: Reasoning-aware and Grounded Explanation
Shi Chen
Qi Zhao
20
18
0
11 Mar 2022
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,724
0
26 Sep 2016
Multimodal Compact Bilinear Pooling for Visual Question Answering and
  Visual Grounding
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
Akira Fukui
Dong Huk Park
Daylen Yang
Anna Rohrbach
Trevor Darrell
Marcus Rohrbach
144
1,464
0
06 Jun 2016
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