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  This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Qwen/Qwen3-VL-Embedding-2B](https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B). It maps sentences & paragraphs to a 2048-dimensional dense vector space and can be used for retrieval.
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  > [!NOTE]
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- > The evaluation results reported in this README were obtained with `max_pixels = 768 * 32 * 32`. When evaluated on **KoViDoRe v2** with `max_pixels = 1800 * 32 * 32`, the NDCG@10 scores are as follows:
 
 
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  > | Domain | NDCG@10 |
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  > | Hr | 0.4107 |
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  > | Economic | 0.2404 |
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  > | **Average** | **0.4905** |
 
 
 
 
 
 
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  ## Model Details
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  This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Qwen/Qwen3-VL-Embedding-2B](https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B). It maps sentences & paragraphs to a 2048-dimensional dense vector space and can be used for retrieval.
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  > [!NOTE]
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+ > The evaluation results reported in this README were obtained with `max_pixels = 1024 * 32 * 32`. When evaluated on **KoViDoRe v2** with `max_pixels = 1800 * 32 * 32`, the NDCG@10 scores are as follows:
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+ > **KoViDoRe v2**
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  >
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  > | Domain | NDCG@10 |
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  > |---|---|
 
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  > | Hr | 0.4107 |
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  > | Economic | 0.2404 |
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  > | **Average** | **0.4905** |
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+ > **SDS KoPub-VDR**
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+ > | Domain | NDCG@10 |
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+ > |---|---|
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+ > | **Average** | **0.6522** |
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  ## Model Details
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