imagenet-1k
M Availability
ImageNet++, no toxic images were found, indicating that the dataset's captions are safe.
A Label is Worth a Thousand Images in Dataset Distillation
Understanding how and why data distillation methods work is vital not only for improving these methods but also for revealing fundamental characteristics of "good" training data.
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- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- North America > United States > California > Santa Clara County > Mountain View (0.04)
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- Research Report > New Finding (1.00)
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- Education (0.69)
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- Information Technology > Artificial Intelligence > Vision (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
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Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection
To speed up ACL, this paper proposes a robustness-aware coreset selection (RCS) method.
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- North America > United States (0.04)
- Asia > Middle East > Israel > Tel Aviv District > Tel Aviv (0.04)
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Elucidating the Design Space of Dataset Condensation
D ataset C ondensation ( EDC), establishes a benchmark for both small and large-scale dataset condensation.
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- Europe > Austria > Vienna (0.14)
- North America > United States > Louisiana > Orleans Parish > New Orleans (0.04)
- North America > United States > Utah > Salt Lake County > Salt Lake City (0.04)
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- Research Report > New Finding (1.00)
- Research Report > Experimental Study (0.93)
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- Europe > Germany > North Rhine-Westphalia > Upper Bavaria > Munich (0.05)
- Asia > China (0.05)
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On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection (Appendix) A Additional experimental results
Description-level outliers include class-relevant information, but when the class label is omitted, they become very vague and difficult to interpret.
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- Government > Military > Air Force (0.68)
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- Transportation > Freight & Logistics Services > Shipping (0.46)