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  • About
    • The mission
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    • External Advisory Board
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    • 10th SmartData@PoliTO Workshop – Present and Future Directions
    • 9th SmartData@PoliTO Workshop – SmartData@PoliTO meets AI-H@PoliTO
    • La biblioteca nel metaverso – la Reading & Machine
  • Workshops
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      • On the dynamics of music virality and its relation with mainstream success
      • Bypass frauds in cellular networks: from Financial strikes to Data poisoning
      • Empowering Data Owners with Control in Outsourcing and Sharing Scenarios
    • SmartTalks
  • Education
    • Courses for PhD students
    • PhD Course: Topological Data Analysis
    • PhD Course: Data Science for Networks
    • Corporate training on Digital Transformation
  • Research
    • Publications
    • Current PhD
    • Projects
    • Open Datasets & Libraries
    • Topics
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    • open position – PhD student
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    • open position – PostDoc researchers
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Home » Publications » M3-VRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding

M3-VRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding

Yihao Ding, Lorenzo Vaiani, Caren Han, Jean Lee, Paolo Garza, Josiah Poon, Luca Cagliero (2024) M3-VRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding, In: Findings of ACL 2024

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