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@@ -27,11 +27,12 @@ OmniEmbed generates unified embeddings across multilingual text, images, audio,
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  | MIRACL | Multilingual Retrieval | nDCG@10 | 69.1 | BGE‑M3 (69.2) |
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  | VIDORE | Image Document Retrieval | nDCG@5 | 85.8 | DSE‑QWen2 (85.8) |
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  | MSRVTT | Video Retrieval | R@1 | 51.3 | CLIP (31.2) |
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- | AudioCaps | Audio Retrieval | R@1 | 34.0 | [*](https://paperswithcode.com/sota/text-to-audio-retrieval-on-audiocaps) |
 
 
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  OmniEmbed achieves strong performance, comparable to models specifically optimized for individual tasks.
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- > Although multiple baselines exist on AudioCaps, we could not identify a consistent query/corpus setting in the literature for direct comparison.
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  | MIRACL | Multilingual Retrieval | nDCG@10 | 69.1 | BGE‑M3 (69.2) |
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  | VIDORE | Image Document Retrieval | nDCG@5 | 85.8 | DSE‑QWen2 (85.8) |
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  | MSRVTT | Video Retrieval | R@1 | 51.3 | CLIP (31.2) |
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+ | AudioCaps | Audio Retrieval | R@1 | 34.0 | [CE](https://paperswithcode.com/sota/text-to-audio-retrieval-on-audiocaps) (23.1) |
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+ > Although multiple baselines exist on AudioCaps, we could not identify a consistent query/corpus setting in the literature for direct comparison.
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  OmniEmbed achieves strong performance, comparable to models specifically optimized for individual tasks.
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