Abstract:Digitizing complex documents with handwritten content, irregular tables, and heterogeneous layouts remains challenging, as traditional Optical Character Recognition (OCR) systems fail to capture writing nuances, author-specific conventions, and document structure, and recent LLM-based approaches lack mechanisms for precise, scalable correction. We present an interactive document digitization system that integrates layout-aware parsing, OCR, and LLM-based reconstruction with user-driven refinement. The system is informed by a formative study that identifies key challenges and interaction needs in real-world digitization workflows. It supports both direct edits and natural-language instructions, and introduces a layout-aware propagation mechanism that generalizes user corrections across structurally similar regions. This enables not only efficient error correction but also document re-shaping into structured, analyzable representations. We evaluate the system through a within-subjects user study (n=12) on real-world documents. Results show improved correction efficiency and reduced repetitive effort, demonstrating more effective and controllable document digitization procedure.
From: Nabin Khanal [view email]
[v1]
Tue, 2 Jun 2026 07:31:46 UTC (21,594 KB)
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。