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--- |
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language: |
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- ar |
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pipeline_tag: visual-question-answering |
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--- |
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# Dallah: A Dialect-Aware Multimodal Large Language Model for Arabic |
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Dallah is an advanced multimodal large language model (MLLM) tailored for the Arabic language, with a specific focus on understanding and generating content across various Arabic dialects. Built upon the **LLaVA** framework and powered by the **LLaMA-2** architecture, Dallah integrates both textual and visual data to facilitate comprehensive multimodal interactions. |
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## Model Details |
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- **Architecture**: LLaVA-based multimodal model with LLaMA-2 backbone. |
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- **Languages Supported**: Modern Standard Arabic (MSA) and six major Arabic dialects. |
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- **Modalities**: Text and image. |
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## Training Data |
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Dallah was fine-tuned on a diverse dataset encompassing both textual and visual information: |
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- **Textual Data**: Includes MSA and six prominent Arabic dialects, ensuring the model's proficiency across different regional linguistic variations. |
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- **Visual Data**: Comprised of image-text pairs, enabling the model to process and generate content that integrates both modalities. |
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## Performance |
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Dallah demonstrates state-of-the-art performance in Arabic MLLMs: |
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- Excels in both MSA and dialectal Arabic benchmarks. |
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- Effectively handles complex multimodal interactions involving textual and visual elements. |
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## Applications |
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Dallah’s multimodal and dialect-aware capabilities make it suitable for a range of applications, including: |
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- **Multilingual Chatbots**: Enhancing user interactions by understanding and responding in specific Arabic dialects. |
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- **Content Creation**: Assisting in generating culturally and linguistically appropriate content for diverse Arabic-speaking audiences. |
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- **Educational Tools**: Supporting language learning by providing examples and explanations in various dialects. |
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- **Cultural Preservation**: Documenting and promoting the use of different Arabic dialects on digital platforms. |
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## Citation |
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If you use Dallah in your research or applications, please cite the following paper: |
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```bibtex |
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@inproceedings{alwajih2024dallah, |
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title={Dallah: A Dialect-Aware Multimodal Large Language Model for Arabic}, |
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author={Alwajih, Fakhraddin and Bhatia, Gagan and Abdul-Mageed, Muhammad}, |
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booktitle={Proceedings of The Second Arabic Natural Language Processing Conference}, |
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pages={320--336}, |
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year={2024}, |
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address={Bangkok, Thailand}, |
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publisher={Association for Computational Linguistics}, |
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url={https://aclanthology.org/2024.arabicnlp-1.27} |
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} |
