Question Answering
Transformers
PyTorch
Arabic
Inference Endpoints
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  ## Technical Specifications
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  Model Architecture and Objective
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- AraDPR utilizes a dual-encoder architecture, with separate encoders for questions and passages. The model is optimized to project semantically related questions and passages closer in the vector space.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Technical Specifications
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  Model Architecture and Objective
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+ AraDPR utilizes a dual-encoder architecture, with separate encoders for questions and passages. The model is optimized to project semantically related questions and passages closer in the vector space.
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+ ## Citation
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+ If you find these codes or data useful, please consider citing our paper as:
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+ ```
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+ @misc{abdallah2024arabicaqa,
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+ title={ArabicaQA: A Comprehensive Dataset for Arabic Question Answering},
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+ author={Abdelrahman Abdallah and Mahmoud Kasem and Mahmoud Abdalla and Mohamed Mahmoud and Mohamed Elkasaby and Yasser Elbendary and Adam Jatowt},
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+ year={2024},
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+ eprint={2403.17848},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+ ```