Heterogeneous Document

Heterogeneous document processing focuses on efficiently extracting information and knowledge from diverse document formats (e.g., PDFs, web pages, emails) which often lack standardized structures. Current research emphasizes developing robust frameworks that leverage techniques like large language models, diffusion models for layout generation, and cross-modal entity matching to overcome challenges posed by this unstructured data. These advancements aim to improve knowledge graph construction, information retrieval, and multi-document summarization, ultimately enabling more effective knowledge discovery and utilization across various domains. The resulting tools and techniques have significant implications for data integration, knowledge management, and information access in both research and industry.