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Vision-Language Models · benchmark dataset · ARABIC

MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering.

Text-Centric Visual Question Answering (TEC-VQA) benchmark featuring high-quality human expert annotations across 9 diverse languages (AR, DE, FR, IT, JA, KO, RU, TH, VI). MTVQA evaluates multimodal large language models on their ability to understand and answer questions about text in images across multiple languages.

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§ 06 · Contribute

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Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

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What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies