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 r
Youtu-Parsing-Omni is a unified multi-modal parser that encodes documents, images, audio, and video into structured spatiotemporal records using shared weights and cross-modal fusion, achieving state-of-the-art results across parsing benchmarks through a self-evolving on-policy distillation…
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 encoder for every modality and one schema for every task. Youtu-Omni-Encoder, initialized from a pre-trained language model to strengthen text reading, encodes all modalities with shared weights in a unified space-time coordinate system, and a few fusion layers let video frames attend to concurrent audio, bringing cross-modal fusion and temporal alignment into perception itself. OmniSchema unifies the outputs of all ten…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Youtu-Parsing-Omni: One Encoder, One Schema, All Modalities was first seen on Hugging Face · Daily papers on Oct 30, 2026. Since then it has appeared in 11 checks on 2 different days. Its best position was #4 of 30, reached on Oct 31, 03:28 UTC. It is #4 right now, climbing from #5 to #4 over the last 6 checks.
Position on Hugging Face · Daily papers at every check (lower is better).
Best rank per day (UTC).
▲ as reported by Hugging Face.
Yes. As of Oct 31, 09:28 UTC it is #4, climbing from #5 to #4 over the last 6 checks.
#4 on Hugging Face · Daily papers, on Oct 31, 03:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 30, 2026 and has been on the list on 2 days (11 checks) since.