Document Retrieval-Aware Chunking (D-RAC): Universal Retrieval-Aware Ingestion of Enterprise Documents via PDF Normalization and Multimodal Markdown Conversion

arXiv:2609.24220 · cs.CV · Submitted 2026-09-21 · Read on arXiv

cs.CV

Submitted: 2026-09-21

Updated: 2026-09-21

Code: https://github.com/udayallu/RAG-Multi-Corpus

Terminology

• RAG — 12× in this paper · explained in 3 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• AGN — 4× in this paper · explained in 1 episode
• Hallucination — 4× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation — 4× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 16 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Web Retrieval-Aware Chunking (W-RAC) for Efficient and Cost-Effective Retrieval-Augmented Generation Systems
• LayoutLM: Pre-training of Text and Layout for Document Image Understanding
• Gemma 3 Technical Report

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