Document Retrieval-Aware Chunking (D-RAC): Universal Retrieval-Aware Ingestion of Enterprise Documents via PDF Normalization and Multimodal Markdown Conversion
- 类型：arxiv
- 标识：2609.24220
- 链接：https://arxiv.org/abs/2609.24220
- 主分类：rag
- 形态：method
- TLDR：Retrieval-Augmented Generation (RAG) systems over enterprise knowledge bases must ingest heterogeneous document formats -- PDFs, Word documents, presentations, and scans -- whose content is locked inside complex visual layouts, multi-column pages, and dense tables. Rule-based extraction and OCR destroy reading order, flatten tables, and lose heading hierarchy, while fully agentic chunking over extracted text incurs high token costs and hallucination risk. We present Document Retrieval-Aware Chunking (D-RAC), an extension of our Web Retrieval-Aware Chunking (W-RAC) framework to arbitrary docume
- 副分类：multimodal
- 待LLM分类：否
- 来源文件：
- /inbox/tom/_candidates/2026-09-22-agent-rag-longcontext-candidates.json