Flipping 1-2 sign bits in DNN parameters, located without data or optimization, drops accuracy to near zero across image classification, detection, segmentation, and language models.
Food-101 – mining discriminative components with random forests
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UNVERDICTED 2representative citing papers
The ADC method automates the creation of large image classification datasets using LLMs and search engines, achieving 79% human agreement and reducing label noise on a 1 million image clothing dataset, while also releasing benchmarks for noise and bias issues.
citing papers explorer
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Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips
Flipping 1-2 sign bits in DNN parameters, located without data or optimization, drops accuracy to near zero across image classification, detection, segmentation, and language models.
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Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond
The ADC method automates the creation of large image classification datasets using LLMs and search engines, achieving 79% human agreement and reducing label noise on a 1 million image clothing dataset, while also releasing benchmarks for noise and bias issues.