POTATR: A Lightweight Image-to-Graph Model for Page-Level Table Extraction
Researchers have developed POTATR, a new lightweight image-to-graph model for extracting tables from documents. This 29 million parameter model significantly outperforms existing methods on the PubTables-v2 benchmark, achieving a GriTS_Con score of 0.964. POTATR is also considerably faster and more cost-effective than current large language models, with its output being spatially grounded for verification and further integration. AI
IMPACT Sets a new standard for efficient and accurate table extraction, potentially accelerating document processing workflows.