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# INQUIRE-Rerank
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# INQUIRE-Rerank
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**Please note that this is dataset is preliminary, and will be updated soon.**
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**INQUIRE: A Natural World Text-to-Image Retrieval Benchmark**
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INQUIRE is a text-to-image retrieval benchmark designed to challenge multimodal models with expert-level queries about the natural world.
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This dataset aims to emulate real world image retrieval and analysis problems faced by scientists working with large-scale image collections.
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Therefore, we hope that INQUIRE will both encourage and track advancements in the real scientific utility of AI systems.
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**Dataset Details**
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The **INQUIRE-Rerank** task fixes an initial ranking of 100 images per query, obtained using CLIP ViT-H-14 zero-shot retrieval on the entire 5 million image iNat24 dataset.
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This fixed starting point makes reranking evaluation consistent, and saves time from running the initial retrieval yourself. If you're interested in full-dataset retrieval,
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check out **INQUIRE-Fullrank**.
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**Dataset Sources**
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- Website: [https://inquire-benchmark.github.io/](https://inquire-benchmark.github.io/)
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- Repository: [https://github.com/inquire-benchmark/INQUIRE](https://github.com/inquire-benchmark/INQUIRE)
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