3 papers
cs.AI2026
ST-Raptor: An Agentic System for Semi-Structured Table QA
Jinxiu Qu, Zirui Tang, Hongzhang Huang +7
Semi-structured table question answering (QA) is a challenging task that requires (1) precise extraction of cell contents and positions and (2) accurate recovery of key implicit lo…
cs.CV2025
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Junbo Niu, Zheng Liu, Zhuangcheng Gu +58
We introduce MinerU2.5, a 1.2B-parameter document parsing vision-language model that achieves state-of-the-art recognition accuracy while maintaining exceptional computational effi…
cs.AI2025
ST-Raptor: LLM-Powered Semi-Structured Table Question Answering
Zirui Tang, Boyu Niu, Xuanhe Zhou +6
Semi-structured tables, widely used in real-world applications (e.g., financial reports, medical records, transactional orders), often involve flexible and complex layouts (e.g., h…