title: Behind Maya: Building a Multilingual Vision Language Model
summary: 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.
paper_authors._id: 68262a5ea5284bb5e477446b
paper_authors.name: Nahid Alam
paper_authors._id: 68262a5ea5284bb5e477446c
paper_authors.name: Karthik Reddy Kanjula
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paper_authors.fullname: Karthik
paper_authors.type: user
paper_authors.user: kkr5155
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paper_authors.name: Surya Guthikonda
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paper_authors.name: Timothy Chung
paper_authors._id: 68262a5ea5284bb5e477446f
paper_authors.name: Bala Krishna S Vegesna
paper_authors._id: 68262a5ea5284bb5e4774470
paper_authors.name: Abhipsha Das
paper_authors._id: 68262a5ea5284bb5e4774471
paper_authors.name: Anthony Susevski
paper_authors._id: 68262a5ea5284bb5e4774472
paper_authors.name: Ryan Sze-Yin Chan
paper_authors.status: claimed_verified
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paper_authors.fullname: Ryan Chan
paper_authors.type: user
paper_authors.user: rchan26
paper_authors._id: 68262a5ea5284bb5e4774473
paper_authors.name: S M Iftekhar Uddin
paper_authors._id: 68262a5ea5284bb5e4774474
paper_authors.name: Shayekh Bin Islam
paper_authors._id: 68262a5ea5284bb5e4774475
paper_authors.name: Roshan Santhosh
paper_authors._id: 68262a5ea5284bb5e4774476
paper_authors.name: Snegha A
paper_authors._id: 68262a5ea5284bb5e4774477
paper_authors.name: Drishti Sharma
paper_authors.status: claimed_verified
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paper_authors._id: 618c1ad1c74578e0a4a4d074
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paper_authors.fullname: Drishti Sharma
paper_authors.type: user
paper_authors.user: DrishtiSharma
paper_authors._id: 68262a5ea5284bb5e4774478
paper_authors.name: Chen Liu
paper_authors._id: 68262a5ea5284bb5e4774479
paper_authors.name: Isha Chaturvedi
paper_authors._id: 68262a5ea5284bb5e477447a
paper_authors.name: Genta Indra Winata
paper_authors._id: 68262a5ea5284bb5e477447b
paper_authors.name: Ashvanth. S
paper_authors._id: 68262a5ea5284bb5e477447c
paper_authors.name: Snehanshu Mukherjee
paper_authors._id: 68262a5ea5284bb5e477447d
paper_authors.name: Alham Fikri Aji
paper_title: Behind Maya: Building a Multilingual Vision Language Model
paper_summary: 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.
paper_ai_summary: Maya, a multilingual Vision-Language Model, enhances performance on low-resource languages and varied cultural contexts using a multilingual image-text pretraining dataset.
paper_ai_keywords: Vision-Language Models multilingual image-text pretraining dataset LLaVA pretraining dataset multilingual image-text model