Update README.md

README.md

@@ -27,9 +27,9 @@ OmniEmbed generates unified embeddings across multilingual text, images, audio,
 | MIRACL    | Multilingual Retrieval   | nDCG@10 | 69.1      | BGE‑M3 (69.2)     |
 | VIDORE    | Image Document Retrieval | nDCG@5  | 85.8      | DSE‑QWen2 (85.8)  |
 | MSRVTT    | Video Retrieval          | R@1     | 51.3      | CLIP (31.2)       |
-| AudioCaps | Audio Retrieval          | R@1     | 34.0      | [CE](https://paperswithcode.com/sota/text-to-audio-retrieval-on-audiocaps) (23.1)       |
+| AudioCaps | Audio Retrieval          | R@1     | 34.0      | *[CE](https://paperswithcode.com/sota/text-to-audio-retrieval-on-audiocaps) (23.1)       |
 
-> Although multiple baselines exist on AudioCaps, we could not identify a consistent query/corpus setting in the literature for direct comparison.
+> * Although multiple baselines exist on AudioCaps, we could not identify a consistent query/corpus setting in the literature for direct comparison.
 
 OmniEmbed achieves strong performance, comparable to models specifically optimized for individual tasks.