LLM Information Extraction

LLM: Large Language Model

Follow this topic Ask about this topic

Momentum

24 papers in the last four weeks, up 243% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 152

All topics

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction
May 4, 2026Sin Yu Bonnie Ho, Arlie Coles, Erik Larsson +3Retrieval-Augmented Generation LLM Inference Acceleration
Microsoft
Effective Performance Measurement: Challenges and Opportunities in KPI Extraction from Earnings Calls
May 4, 2026Rasmus T. Aavang, Rasmus Tjalk-Bøggild, Alexandre Iolov +3Document Information Extraction LLM Information Extraction
Department of Computer Science, Aalborg University, Denmark · ALIPES ApS, Denmark · University of Copenhagen
BIM Information Extraction Through LLM-based Adaptive Exploration
May 3, 2026Sylvain Hellin, Suhyung Jang, Stefan Fuchs +2Building Information Modeling LLM Information Extraction
Chair of Computing in Civil and Building Engineering, Georg Nemetschek Institute, Technical University of Munich, Munich, Germany
From Unstructured Recall to Schema-Grounded Memory: Reliable AI Memory via Iterative, Schema-Aware Extraction
Apr 30, 2026Alex Petrov, Alexander Gusak, Denis Mukha +1LLM Memory Document Information Extraction
1xmemory
Breaking the Autoregressive Chain: Hyper-Parallel Decoding for Efficient LLM-Based Attribute Value Extraction
Apr 29, 2026Theodore Glavas, Nikhita Vedula, Dushyanta Dhyani +2LLM Inference Acceleration Parallel Decoding
Amazon.com, Inc. · McGill University · Mila - Quebec AI Institute +1
The Structured Output Benchmark: A Multi-Source Benchmark for Evaluating Structured Output Quality in Large Language Models
Apr 28, 2026Abhinav Kumar Singh, Harsha Vardhan Khurdula, Yoeven D Khemlani +1LLM Evaluation LLM Information Extraction
1New Delhi, India · JigsawStack, Inc. 2San Francisco, CA, USA · 3Durgapur, WB, India
Large language model-enabled automated data extraction for concrete materials informatics
Apr 24, 2026Zhanzhao Li, Kengran Yang, Qiyao He +1LLM Information Extraction
Department of Civil and Environmental Engineering, Rice University, Houston, TX 77005, USA. · Rice Advanced Materials Institute, Rice University, Houston, TX 77005, USA. · Ken Kennedy Institute, Rice University, Houston, TX 77005, USA. +1
Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their Limitations
Apr 24, 2026Anna Arnaudo, Riccardo Coppola, Maurizio Morisio +4Requirements Engineering LLM Prompting
Department of Control and Computer Engineering, Politecnico di Torino · Politecnico di Torino
A Multimodal Text- and Graph-Based Approach for Open-Domain Event Extraction from Documents
Apr 23, 2026Praval SharmaDocument Information Extraction LLM Information Extraction
College of Information Science & Technology University of Nebraska Omaha, USA
Job Skill Extraction via LLM-Centric Multi-Module Framework
Apr 23, 2026Guojing Li, Zichuan Fu, Junyi Li +8Document Information Extraction LLM Information Extraction
City University of Hong Kong · Renmin University of China · 1City University of Hong Kong. +1
BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature
Apr 23, 2026Jiaxian Yan, Jintao Zhu, Yuhang Yang +8Document Information Extraction Multimodal Large Language Models
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China · Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University · Princeton University +2
Serialisation Strategy Matters: How FHIR Data Format Affects LLM Medication Reconciliation
Apr 22, 2026Sanjoy PatorHealthcare LLM Information Extraction
Independent Researcher
Benchmarking Large Language Models for Safety Data Extraction
Apr 22, 2026Jonas Grill, Thomas Bayer, Sören BerlingerLLM Evaluation LLM Prompting
1SAP SE, Germany. · Institute for Digital Transformation, Ravensburg-Weingarten University.
Construction of Knowledge Graph based on Language Model
Apr 21, 2026Qiubai Zhu, Qingwang Wang, Haibin Yuan +2KG Construction LLM Information Extraction
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China · Yunnan Key Laboratory of Computer Technologies Application, Kunming University of Science and Technology, Kunming 650500, China · Tin Branch, Yunnan Tin Co., LTD.
Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs
Apr 20, 2026Ruixuan Liu, David Evans, Li XiongLLM Auditing Privacy Leakage in Language Models
Emory University · University of Virginia
Improving the Completeness and Comparability of Segment Disclosures: A Large Language Model Approach
Apr 20, 2026Yue Liu, Zhiyuan Cheng, Longying LaiDocument Information Extraction LLM Information Extraction
RutgersRutgersUniversityBusiness -SchoolNewark · SchoolStanfordof EngineeringUniversity · Simon Business School University of Rochester Rochester, NY, USA
Beyond the Basics: Leveraging Large Language Model for Fine-Grained Medical Entity Recognition
Apr 19, 2026Nwe Ni Win, Jim Basilakis, Steven Thomas +6Named Entity Recognition Healthcare
Western Sydney University, Sydney, Australia · Western Sydney University, Australia · South Western Emergency Research Institute, Sydney, Australia +7
Comparing Human and Large Language Model Interpretation of Implicit Information
Apr 18, 2026Antonio De Santis, Tommaso Bonetti, Andrea Tocchetti +1Implicit Reasoning in Language Models LLM Information Extraction
Politecnico di Milano, Italy
From "Strings" to "Things" for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems
Apr 18, 2026Abhirup Dasgupta, Fernando Spadea, Oshani SeneviratneKG Construction Knowledge Representation
Rensselaer Polytechnic Institute, Troy NY 12180, USA
MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning
Apr 18, 2026Ruijun Huang, Zhiqiao Kang, Yuxuan Zhu +5LLM Hallucination Mitigation Document Information Extraction
1Shenzhen Key Laboratory for High Performance Data Mining, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences · Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology
CBRS: Cognitive Blood Request System with Bilingual Dataset and Dual-Layer Filtering for Multi-Platform Social Streams
Apr 17, 2026Anik Saha, Mst. Fahmida Sultana Naznin, Zia Ul Hassan Abdullah +3LLM Information Extraction
Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition
Apr 17, 2026Siun Kim, Hyung-Jin YoonNamed Entity Recognition LLM-Assisted Annotation
Seltasquare Seoul, Korea · Biomedical Research Institute, Seoul National University Hospital · Seoul National University College of Medicine Seoul, Korea
IE as Cache: Information Extraction Enhanced Agentic Reasoning
Apr 16, 2026Hang Lv, Sheng Liang, Hongchao Gu +5Agentic Reasoning LLM Information Extraction
University of Science and Technology of China · Huawei Technologies Co., Ltd.
ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery
Apr 10, 2026Shahar Levy, Eliya Habba, Reshef Mintz +3LLM-Assisted Annotation Document Information Extraction
School of Computer Science and Engineering, The Hebrew University of Jerusalem · Faculty of Law, The Hebrew University of Jerusalem · Allen Institute for AI
A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization
Apr 1, 2026Maxwell J. Jacobson, Daniel Xie, Jackson Shen +6Multi-Agent LLM Systems AI-Assisted Scientific Research
Department of Computer Science, Purdue University, IN, USA · School of Materials Science and Engineering, Purdue University, IN, USA
SeaAlert: Robust Severity Classification and LLM-Based Information Extraction for Noisy Maritime Distress Communications
Mar 23, 2026Tomer Atia, Yehudit Aperstein, Alexander ApartsinLLM Information Extraction Language Model Robustness
School of Computer Science, Faculty of Sciences, HIT-Holon Institute of Technology, Holon 58102, Israel · Intelligent Systems, Afeka Academic College of Engineering, Tel Aviv 69988, Israel
LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes
Mar 14, 2026Mingchen Shao, Yuzhang Xie, Carl Yang +1Alzheimer's Disease Clinical Information Extraction
Northwestern University, Evanston, IL · Emory University, Atlanta, GA
Do not be greedy, Think Twice: Sampling and Selection for Document-level Information Extraction
Jan 26, 2026Mikel Zubillaga, Oscar Sainz, Oier Lopez de Lacalle +1Self-Consistency Decoding Document Information Extraction
HiTZ Center - Ixa, University of the Basque Country UPV/EHU
Strategies for Span Labeling with Large Language Models
Jan 23, 2026Danil Semin, Ondřej Dušek, Zdeněk KasnerConstrained Decoding Language Model Decoding
Institute of Formal and Applied Linguistics Faculty of Mathematics and Physics, Charles University
LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature
Oct 28, 2025Magdalena Lederbauer, Siddharth Betala, Valerie Gentzke +22Document Information Extraction Materials Science
Entalpic · ENSA Lyon UMR-MAP Aria · Independent Researcher +8

May 4, 2026, cs.IRJ/K move · Enter open · S save

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction

Sin Yu Bonnie Ho, Arlie Coles, Erik Larsson, Eric Marshall+2

Microsoft

Retrieval-Augmented Generation LLM Inference Acceleration LLM Information Extraction

Open paper AskPDF arXiv

Extracting structured data from unstructured text using large language models (LLMs) becomes challenging when target schemas are large and complex. In such cases, including the full schema in the prompt increases cost and latency, risks lost-in-the-middle performance degradation, and can exceed context length limits. We propose SchemaRAG, a retrieval-augmented generation (RAG) framework that dynamically prunes the output schema space for schema-conditioned information extraction tasks by leveraging schema metadata and few-shot examples when available. We evaluate SchemaRAG on real-world healthcare and e-commerce datasets. Our results show that SchemaRAG can achieve up to an 8.8% increase in micro-F1, a 47% reduction in latency, and a 48% reduction in token costs, demonstrating its practicality for large-schema extraction.

Momentum

Related topics

Latest papers 152