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 Computation and Language
Sep 10
Scaling E-Commerce Attribute Extraction with Parallel Decoding
The paper presents a two‑stage large language model pipeline for e‑commerce attribute extraction. First, it discovers a compact, ranked set of purchase‑discriminative attributes for each product category; second, it extracts those attribute values from catalog text using a fine‑tuned Qwen3‑4B model with Hyper‑Parallel Decoding. The approach attains 85% extraction accuracy while cutting inference costs by 92%, enabling scalable production use and producing consistent, comparable product knowledge bases.
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
Sep 15
TEAR: Table Extraction with Attribute Recommendation from Texts via Large Language Models
arXiv:2609.15205v1 Announce Type: cross Abstract: Table extraction from texts is an important task for information systems, and recent approaches that prompt large language models (LLMs) with instruc...
Hugging Face Trending Papers
Aug 24
Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records
The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to produce a fully machine-actionable graph in which ev...
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.