Logics-Parsing-Omni Technical Report
Addressing the challenges of fragmented task definitions and the heterogeneity of unstructured data in multimodal parsing, this paper proposes the Omni Parsing framework. This framework establishes a Unified Taxonomy covering documents, images, and audio-visual streams, introducing a progressive parsing paradigm that bridges perception and cognition. Specifically, the framework integrates three hierarchical levels: 1) Holistic Detection, which achieves precise spatial-temporal grounding of objects or events to establish a geometric baseline for perception; 2) Fine-grained Recognition, which performs symbolization (e.g., OCR/ASR) and attribute extraction on localized objects to complete st...
| Authors | Xin An, Jingyi Cai, Xiangyang Chen et al. |
|---|---|
| Primary category | cs.AI |
| Published | 10 March 2026 |
| Last updated at source | 8 April 2026 |
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