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New Omni-Modal Parser Youtu-Parsing-Omni Handles Text, Image, Audio, Video

Researchers have introduced Youtu-Parsing-Omni, an omni-modal parser capable of converting documents, images, audio, and video into structured, spatio-temporal records. This system utilizes a single encoder for each modality, with shared weights in a unified coordinate system, and employs fusion layers for cross-modal attention. A unified OmniSchema and a self-evolving distillation procedure, OSAD, allow for co-evolution of the parser and its supervision. The 5 billion parameter model achieves state-of-the-art results on OmniDocBench and OmniParsingBench, particularly excelling in audio and video tasks, and also demonstrates strong performance in chart parsing and music transcription. AI

IMPACT This model advances agent perception by enabling evidence citation across diverse data types, potentially improving multimodal reasoning capabilities.

RANK_REASON The cluster describes a new research paper detailing an omni-modal parser with code and model weights released. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Omni-Modal Parser Youtu-Parsing-Omni Handles Text, Image, Audio, Video

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The cluster describes a new research paper detailing an omni-modal parser with code and model weights released. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Youtu-Parsing-Omni: One Encoder, One Schema, All Modalities

    We present Youtu-Parsing-Omni, an omni-modal parser that converts documents, images, audio, and video into structured records grounded in space and time, providing a perception layer for agents that read, locate, and cite evidence across modalities. Its design rests on one encode…