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Datasets:
kailinjiang
/
EVOKE

Tasks:
Image-Text-to-Text
Modalities:
Image
Formats:
imagefolder
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1K - 10K
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πŸ€— Benchmark

To evaluate evolving knowledge injection in LMMs, we propose a pipeline to automatically collect evolving knowledge, constructing the EVOlving KnowledgE (EVOKE) benchmark. The EVOKE benchmark comprises 9,422 knowledge-image pairs for LMM knowledge injection, spanning 159 fine-grained types (29 New types and 130 Entity types), highlighting its diversity.

https://arxiv.org/abs/2505.24449

You can download EVOKE πŸ€—. And the expected structure of files is:

EVOKE
|-- json/jsonl
|   |-- evoke_injection_data.json
|   |-- evoke_evaluation_data.jsonl
|-- imgs
|   |-- injection
|   |   |-- evoke_entity_injection_imgs.zip
|   |   |-- evoke_news_injection_imgs.zip
|   |-- evaluation
|   |   |-- evoke_news_evaluation_imgs.zip
|   |   |-- evoke_entity_evaluation_imgs.zip
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