Navigating Continual Test-time Adaptation with Symbiosis Knowledge
Authors: Xu Yang, Moqi Li, Jie Yin, Kun Wei, Cheng Deng
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experimental results demonstrate that our method achieves state-of-the-art performance on several benchmark datasets. |
| Researcher Affiliation | Academia | Xu Yang , Moqi Li , Jie Yin , Kun Wei and Cheng Deng Xidian University {xuyang.xd, moqili14, weikunsk, chdeng.xd}@gmail.com, yinjie xidian@163.com |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link to open-source code for the described methodology. |
| Open Datasets | Yes | We adopt CIFAR10, CIFAR100, and Image Net as the source domain datasets, and CIFAR10C, CIFAR100C, and Image Net-C as the corresponding target domain datasets, respectively. |
| Dataset Splits | No | The paper does not explicitly provide training/validation/test dataset splits. It describes the use of test-time adaptation on continually changing target domains, and provides sample counts per corruption type for these target domains ('for each corruption, we use 10000 images for both CIFAR10C and CIFAR100C datasets and 5000 images for Image Net-C'), but not a standard validation split for reproducibility of the adaptation process itself. |
| Hardware Specification | No | The paper does not specify any hardware details (e.g., GPU/CPU models, memory, or cloud instances) used for running the experiments. |
| Software Dependencies | No | The paper mentions using 'Adam to optimize the network' but does not provide specific version numbers for Adam or any other software libraries or frameworks used in the implementation. |
| Experiment Setup | Yes | We use Adam to optimize the network and set the learning rate to 1e-3. The data augmentation strategy is the same as [Wang et al., 2022], including color jitter, gaussian blur, gaussian noise, random affine, and random horizontal flip. ... The relaxation factor δ is set as 0.2, λ1 = 0.1 and λ2 = 1 in our experiments. We set βl = 1 e 5l / 1+e 5l and l is the number of layers. |