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Michael Cogswell
Michael Cogswell
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Year
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
200422017
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
4802016
Reducing overfitting in deep networks by decorrelating representations
M Cogswell, F Ahmed, R Girshick, L Zitnick, D Batra
arXiv preprint arXiv:1511.06068, 2015
4702015
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
2972015
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
2212018
Proceedings of the IEEE international conference on computer vision
RR Selvaraju, M Cogswell, A Das, R Vedantam, D Parikh, D Batra
Proceedings of the IEEE international conference on computer vision [J], 2017
1972017
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
1952016
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, 2022
792022
Emergence of compositional language with deep generational transmission
M Cogswell, J Lu, S Lee, D Parikh, D Batra
arXiv preprint arXiv:1904.09067, 2019
532019
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
462012
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
282021
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
232014
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
122020
Unpacking large language models with conceptual consistency
P Sahu, M Cogswell, Y Gong, A Divakaran
arXiv preprint arXiv:2209.15093, 2022
92022
Dress: Instructing large vision-language models to align and interact with humans via natural language feedback
Y Chen, K Sikka, M Cogswell, H Ji, A Divakaran
arXiv preprint arXiv:2311.10081, 2023
72023
Measuring and improving chain-of-thought reasoning in vision-language models
Y Chen, K Sikka, M Cogswell, H Ji, A Divakaran
arXiv preprint arXiv:2309.04461, 2023
72023
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
52021
Grad 鄄 cam: visual explanations from deep networks via gradient 鄄 based localization
RR SELVARAJU, M COGSWELL, A DAS
椅 Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern …, 2017
52017
Probing Conceptual Understanding of Large Visual-Language Models
MC Schiappa, M Cogswell, A Divakaran, YS Rawat
arXiv preprint arXiv:2304.03659, 2023
42023
Comprehension Based Question Answering using Bloom's Taxonomy
P Sahu, M Cogswell, S Rutherford-Quach, A Divakaran
arXiv preprint arXiv:2106.04653, 2021
42021
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