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Michael Cogswell
Michael Cogswell
確認したメール アドレス: sri.com - ホームページ
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引用先
引用先
Grad-cam: Visual explanations from deep networks via gradient-based localization
RR Selvaraju, M Cogswell, A Das, R Vedantam, D Parikh, D Batra
Proceedings of the IEEE international conference on computer vision, 618-626, 2017
127042017
Reducing overfitting in deep networks by decorrelating representations
M Cogswell, F Ahmed, R Girshick, L Zitnick, D Batra
arXiv preprint arXiv:1511.06068, 2015
3802015
Diverse beam search: Decoding diverse solutions from neural sequence models
AK Vijayakumar, M Cogswell, RR Selvaraju, Q Sun, S Lee, D Crandall, ...
arXiv preprint arXiv:1610.02424, 2016
3592016
Why m heads are better than one: Training a diverse ensemble of deep networks
S Lee, S Purushwalkam, M Cogswell, D Crandall, D Batra
arXiv preprint arXiv:1511.06314, 2015
2312015
Stochastic multiple choice learning for training diverse deep ensembles
S Lee, S Purushwalkam Shiva Prakash, M Cogswell, V Ranjan, ...
Advances in Neural Information Processing Systems 29, 2016
1622016
Diverse beam search for improved description of complex scenes
A Vijayakumar, M Cogswell, R Selvaraju, Q Sun, S Lee, D Crandall, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
1512018
Proceedings of the IEEE international conference on computer vision
RR Selvaraju, M Cogswell, A Das, R Vedantam, D Parikh, D Batra
IEEE, 2017
1312017
Grad-CAM: Visual explanations from deep networks via gradient-based localization. arXiv 2016
RR Selvaraju, M Cogswell, A Das, R Vedantam, D Parikh, D Batra
arXiv preprint arXiv:1610.02391, 0
48
Emergence of compositional language with deep generational transmission
M Cogswell, J Lu, S Lee, D Parikh, D Batra
arXiv preprint arXiv:1904.09067, 2019
472019
Running students' software tests against each others' code: new life for an old" gimmick"
SH Edwards, Z Shams, M Cogswell, RC Senkbeil
Proceedings of the 43rd ACM technical symposium on Computer Science …, 2012
422012
Combining the best of graphical models and convnets for semantic segmentation
M Cogswell, X Lin, S Purushwalkam, D Batra
arXiv preprint arXiv:1412.4313, 2014
222014
Trigger hunting with a topological prior for trojan detection
X Hu, X Lin, M Cogswell, Y Yao, S Jha, C Chen
arXiv preprint arXiv:2110.08335, 2021
82021
Dialog without dialog data: Learning visual dialog agents from VQA data
M Cogswell, J Lu, R Jain, S Lee, D Parikh, D Batra
Advances in Neural Information Processing Systems 33, 19988-19999, 2020
82020
Improving users' mental model with attention‐directed counterfactual edits
K Alipour, A Ray, X Lin, M Cogswell, JP Schulze, Y Yao, GT Burachas
Applied AI Letters 2 (4), e47, 2021
42021
Knowing what VQA does not: pointing to error-inducing regions to improve explanation helpfulness
A Ray, M Cogswell, X Lin, K Alipour, A Divakaran, Y Yao, G Burachas
arXiv preprint arXiv 2103, 2021
32021
Generating and evaluating explanations of attended and error‐inducing input regions for VQA models
A Ray, M Cogswell, X Lin, K Alipour, A Divakaran, Y Yao, G Burachas
Applied AI Letters 2 (4), e51, 2021
22021
ABHISHEK DAS
AK DAS, E JORA
22011
Unpacking Large Language Models with Conceptual Consistency
P Sahu, M Cogswell, Y Gong, A Divakaran
arXiv preprint arXiv:2209.15093, 2022
12022
Comprehension Based Question Answering using Bloom's Taxonomy
P Sahu, M Cogswell, S Rutherford-Quach, A Divakaran
arXiv preprint arXiv:2106.04653, 2021
12021
Understanding Representations and Reducing their Redundancy in Deep Networks
MA Cogswell
Virginia Tech, 2016
12016
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論文 1–20