arXiv AI
Jun 2
HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings
arXiv:2502. 15411v4 Announce Type: replace-cross Abstract: Accurate tagging of earnings reports can yield significant short-term returns for stakeholders.
Structured Data Extraction from Real Estate Documents using Clustering, Classification, and Large Language Models
Real estate property listings expose structured metadata through the API. Still, the richest property-level information (i.
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arXiv AI
Aug 3
ExtractBench: A Benchmark for Schema-Guided Enterprise Document Extraction
arXiv:2607. 29677v1 Announce Type: new Abstract: Enterprise workflows increasingly rely on agents for \emph{schema-guided extraction}: given a document and a user-defined schema, the agent faithfully follows the schema to produce the correct output with source evidence as grounding metadata.
arXiv AI
Jul 2
SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction
arXiv:2607. 00008v1 Announce Type: cross Abstract: Extracting structured data from unstructured text using large language models (LLMs) becomes challenging when target schemas are large and complex.
arXiv AI
Aug 7
Schema-Guided Hierarchical Information Extraction and Semantic Evaluation Using Generative AI
arXiv:2608. 06167v1 Announce Type: new Abstract: We present a schema-based framework for extracting complex, structured information from unstructured text documents using generative AI, followed by automated semantic evaluation of the extracted information against a gold standard.
arXiv AI
Aug 3
An Ontology-Guided, Deduplication-Aware Extraction Layer for Knowledge Graph Construction from Heterogeneous Documents
arXiv:2607. 28662v1 Announce Type: new Abstract: Large language models extract entities and relationships from unstructured documents fluently but inconsistently: type vocabularies fracture across documents, the same person surfaces under several name variants, relationships duplicate, and distinct individuals who share a name risk silent conflation.
arXiv AI
Jul 20
DECODEM: Data Extraction from Corporate Organizational Documents via Enhanced Methods
arXiv:2607. 15879v1 Announce Type: cross Abstract: Much empirical legal research depends on translating unstructured text into structured variables.
arXiv AI
Jun 17
Brick-DICL: Dynamic In-Context Learning for Automated Brick Schema Classification
arXiv:2606. 17637v1 Announce Type: new Abstract: Building Management Systems (BMS) are essential for optimizing energy efficiency and operational performance in modern buildings.
Hugging Face Trending Papers
Jun 25
LLM-Based Examination of Eligibility Criteria from Securities Prospectuses at the German Central Bank
Verifying the eligibility of securities as collateral is a key responsibility of the German Central Bank. However, manually verifying these assets against legal and financial criteria within lengthy, semi-structured, and often bilingual prospectuses is a resource-intensive task.
arXiv AI
Jun 30
Sustainable Hybrid Document-Routed Retrieval for Financial RAG: Resolving the Robustness-Precision Trade-off
arXiv:2603. 26815v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) systems for financial document QA typically follow a chunk-based paradigm: documents are split into fragments, embedded, and retrieved by similarity.
Hugging Face Trending Papers
Jun 4
Benchmarking Open-Source Layout Detection Models for Data Snapshot Extraction from Institutional Documents
Institutional documents contain substantial amounts of operational and analytical information embedded within figures and tables. Current approaches for extracting visual content from documents are largely built around generic document layout analysis, where figures and tables are treated as uniformly relevant document objects rather than semantically meaningful analytical artifacts.
arXiv AI
Jul 22
M-RAG: Semantic Key-Value Indexing for Retrieval-Augmented Generation
arXiv:2603. 26667v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) turns external documents into evidence for large language models.
arXiv AI
Jun 24
AI-PAVE-Br: Leveraging Large Language Models for Enhanced Product Attribute Value Extraction through a Golden Set Approach
arXiv:2606. 24655v1 Announce Type: cross Abstract: The explosive growth and complexity of product data within the dynamic Brazilian e-commerce landscape demand robust and specialized methods for structured information extraction.