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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.08910 |
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| _version_ | 1866912376522014720 |
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| author | Alam, Nahid Kanjula, Karthik Reddy Guthikonda, Surya Chung, Timothy Vegesna, Bala Krishna S Das, Abhipsha Susevski, Anthony Chan, Ryan Sze-Yin Uddin, S M Iftekhar Islam, Shayekh Bin Santhosh, Roshan A, Snegha Sharma, Drishti Liu, Chen Chaturvedi, Isha Winata, Genta Indra S, Ashvanth. Mukherjee, Snehanshu Aji, Alham Fikri |
| author_facet | Alam, Nahid Kanjula, Karthik Reddy Guthikonda, Surya Chung, Timothy Vegesna, Bala Krishna S Das, Abhipsha Susevski, Anthony Chan, Ryan Sze-Yin Uddin, S M Iftekhar Islam, Shayekh Bin Santhosh, Roshan A, Snegha Sharma, Drishti Liu, Chen Chaturvedi, Isha Winata, Genta Indra S, Ashvanth. Mukherjee, Snehanshu Aji, Alham Fikri |
| contents | In recent times, we have seen a rapid development of large Vision-Language Models (VLMs). They have shown impressive results on academic benchmarks, primarily in widely spoken languages but lack performance on low-resource languages and varied cultural contexts. To address these limitations, we introduce Maya, an open-source Multilingual VLM. Our contributions are: 1) a multilingual image-text pretraining dataset in eight languages, based on the LLaVA pretraining dataset; and 2) a multilingual image-text model supporting these languages, enhancing cultural and linguistic comprehension in vision-language tasks. Code available at https://github.com/nahidalam/maya. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_08910 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Behind Maya: Building a Multilingual Vision Language Model Alam, Nahid Kanjula, Karthik Reddy Guthikonda, Surya Chung, Timothy Vegesna, Bala Krishna S Das, Abhipsha Susevski, Anthony Chan, Ryan Sze-Yin Uddin, S M Iftekhar Islam, Shayekh Bin Santhosh, Roshan A, Snegha Sharma, Drishti Liu, Chen Chaturvedi, Isha Winata, Genta Indra S, Ashvanth. Mukherjee, Snehanshu Aji, Alham Fikri Computer Vision and Pattern Recognition Computation and Language In recent times, we have seen a rapid development of large Vision-Language Models (VLMs). They have shown impressive results on academic benchmarks, primarily in widely spoken languages but lack performance on low-resource languages and varied cultural contexts. To address these limitations, we introduce Maya, an open-source Multilingual VLM. Our contributions are: 1) a multilingual image-text pretraining dataset in eight languages, based on the LLaVA pretraining dataset; and 2) a multilingual image-text model supporting these languages, enhancing cultural and linguistic comprehension in vision-language tasks. Code available at https://github.com/nahidalam/maya. |
| title | Behind Maya: Building a Multilingual Vision Language Model |
| topic | Computer Vision and Pattern Recognition Computation and Language |
| url | https://arxiv.org/abs/2505.08910 |