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bibtex to link to the paper page https://huggingface.co/papers/2407.20750

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@@ -22,4 +22,17 @@ Model weights for the final JaColBERTv2.5 checkpoint, using an entirely overhaul
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  This model largely outperforms all previous approaches, including JaColBERTV2 multilingual models such as BGE-M3, on all datasets.
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- This page will be updated with the full details and the model report in the next few days.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  This model largely outperforms all previous approaches, including JaColBERTV2 multilingual models such as BGE-M3, on all datasets.
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+ This page will be updated with the full details and the model report in the next few days.
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+ ```
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+ @misc{clavié2024jacolbertv25optimisingmultivectorretrievers,
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+ title={JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resources},
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+ author={Benjamin Clavié},
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+ year={2024},
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+ eprint={2407.20750},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.IR},
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+ url={https://arxiv.org/abs/2407.20750},
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+ }
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+ ```