Researchers have developed EviProp, a novel method for retrieving relevant pages from long, visually rich documents. Unlike existing approaches that score pages independently, EviProp models documents as multimodal Chunk-Page graphs. It uses seeded relevance diffusion, combining query-page similarity with chunk-level signals to improve retrieval accuracy. Experiments on benchmark datasets show EviProp outperforms traditional methods and leads to better downstream question-answering performance. AI
IMPACT Enhances retrieval accuracy for complex multimodal documents, potentially improving AI systems that rely on document understanding.
RANK_REASON This is a research paper describing a new method for document retrieval. [lever_c_demoted from research: ic=1 ai=1.0]
Read on arXiv cs.IR (Information Retrieval) →
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →