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SotA/Natural Language Processing/Prompt Engineering/ImageNet-A

Prompt Engineering on ImageNet-A

Metric: Top-1 accuracy % (higher is better)

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#Model↕Top-1 accuracy %▼Extra DataPaperDate↕Code
1POMP51.6NoPrompt Pre-Training with Twenty-Thousand Classes...2023-04-10Code
2MMRL51.2NoMMRL: Multi-Modal Representation Learning for Vi...2025-03-11Code
3HPT++51.18NoHPT++: Hierarchically Prompting Vision-Language ...2024-08-27Code
4MaPLe50.9NoMaPLe: Multi-modal Prompt Learning2022-10-06Code
5PromptSRC50.9NoSelf-regulating Prompts: Foundational Model Adap...2023-07-13Code
6HPT50.85NoLearning Hierarchical Prompt with Structured Lin...2023-12-11Code
7CoCoOp50.63NoConditional Prompt Learning for Vision-Language ...2022-03-10Code
8CoPrompt50.5NoConsistency-guided Prompt Learning for Vision-La...2023-06-01Code
9CLIP47.77NoLearning Transferable Visual Models From Natural...2021-02-26Code