Safe Distillation Box
Authors: Jingwen Ye, Yining Mao, Jie Song, Xinchao Wang, Cheng Jin, Mingli Song3117-3124
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments across various datasets and architectures demonstrate that, with SDB, the performance of an unauthorized KD drops significantly while that of an authorized gets enhanced, demonstrating the effectiveness of SDB. |
| Researcher Affiliation | Collaboration | Jingwen Ye1,2, Yining Mao1, Jie Song1, Xinchao Wang2, Cheng Jin3, Mingli Song1,4 1 Zhejiang University 2 National University of Singapore 3 Fudan University 4 Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies |
| Pseudocode | No | The paper describes the SDB framework and its strategies (key embedding, knowledge disturbance, knowledge preservation) but does not provide structured pseudocode or an algorithm block. |
| Open Source Code | No | The paper does not contain any explicit statement about releasing source code or a link to a code repository. |
| Open Datasets | Yes | Two public datasets are employed in the experiments, including the CIFAR10 dataset and CIFAR100 dataset. |
| Dataset Splits | No | The paper mentions using CIFAR10 and CIFAR100 datasets for experiments but does not explicitly provide the train/validation/test split percentages or sample counts in the main text. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | We used Py Torch framework for the implementation. |
| Experiment Setup | Yes | For optimizing the SDB models, we used stochastic gradient descent with momentum of 0.9 and learning rate of 0.1 for 200 epochs. For applying distillation, we set T = 4 for CIFAR10 dataset and T = 20 for CIFAR100 dataset. In the random key generation, we set λ = 0.5. In the knowledge disturbance, we set Tdis = 4 for CIFAR10 dataset and Tdis = 20 for CIFAR100 dataset. |