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08/07/2023
Scaling may be all you need for achieving human-level object recognition capacity with human-like visual experience
This paper asks whether current self-supervised learning methods, if suf...
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05/24/2023
What can generic neural networks learn from a child's visual experience?
Young children develop sophisticated internal models of the world based ...
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03/30/2023
Recognition, recall, and retention of few-shot memories in large language models
The training of modern large language models (LLMs) takes place in a reg...
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04/27/2022
Can deep learning match the efficiency of human visual long-term memory in storing object details?
Humans have a remarkably large capacity to store detailed visual informa...
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09/30/2021
Compositional generalization in semantic parsing with pretrained transformers
Large-scale pretraining instills large amounts of knowledge in deep neur...
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09/23/2021
How much "human-like" visual experience do current self-supervised learning algorithms need to achieve human-level object recognition?
This paper addresses a fundamental question: how good are our current se...
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07/31/2020
Self-supervised learning through the eyes of a child
Within months of birth, children have meaningful expectations about the ...
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07/17/2019
Robustness properties of Facebook's ResNeXt WSL models
We investigate the robustness properties of ResNeXt image recognition mo...
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06/20/2019
Improving the robustness of ImageNet classifiers using elements of human visual cognition
We investigate the robustness properties of image recognition models equ...
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05/31/2019
Improved memory in recurrent neural networks with sequential non-normal dynamics
Training recurrent neural networks (RNNs) is a hard problem due to degen...
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05/21/2018
A Simple Cache Model for Image Recognition
Training large-scale image recognition models is computationally expensi...
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01/31/2017