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@@ -190,7 +190,7 @@ We evaluate our model on the small development sets of [mMARCO](https://huggingf
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| 8 | **ColBERT-XM** (ours) | multi-vector | 6.4M | 277M | 37.2 | 28.5 | 26.9 | 26.5 | 27.6 | 26.3 | 27.0 | 25.1 | 24.6 | 24.1 | 27.5 | 22.6 | 23.8 | 19.5 | 26.2 |
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- **Mr. TyDi**:
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| 8 | **ColBERT-XM** (ours) | multi-vector | 6.4M | 277M | 37.2 | 28.5 | 26.9 | 26.5 | 27.6 | 26.3 | 27.0 | 25.1 | 24.6 | 24.1 | 27.5 | 22.6 | 23.8 | 19.5 | 26.2 |
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- **Mr. TyDi**:
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We also evaluate our model on the test set of [Mr. TyDi](https://huggingface.co/datasets/castorini/mr-tydi), another multilingual open retrieval dataset including low-resource languages not present in mMARCO. Below, we compared its performance with other retrieval models on the official dataset metrics, i.e., mean reciprocal rank at cut-off 100 (MRR@100) and recall at cut-off 100 (R@100).
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