Imagen de Portada

Problem Solved? Information Extraction Design Space for Layout-Rich Documents using LLMs

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Colakoglu, Gaye, Solmaz, Gürkan, Fürst, Jonathan
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

AgenticIE: An Adaptive Agent for Information Extraction from Complex Regulatory Documents
por: Colakoglu, Gaye, et al.
Publicado: (2025)

TextMineX: Data, Evaluation Framework and Ontology-guided LLM Pipeline for Humanitarian Mine Action
por: Zhou, Chenyue, et al.
Publicado: (2025)

A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents
por: Adnan, Wiam, et al.
Publicado: (2024)

From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
por: Dinucu-Jianu, David, et al.
Publicado: (2025)

Tabular PDF Information Extraction with Local LLMs and Layout-Aware Parsing: A Reliability Evaluation
por: Hilmi, Muhammad Anis Al, et al.
Publicado: (2026)

Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models
por: Zhu, Wanrong, et al.
Publicado: (2024)

VersionRAG: Version-Aware Retrieval-Augmented Generation for Evolving Documents
por: Huwiler, Daniel, et al.
Publicado: (2025)

RE$^2$: Region-Aware Relation Extraction from Visually Rich Documents
por: Ramu, Pritika, et al.
Publicado: (2023)

Layout-Aware Parsing Meets Efficient LLMs: A Unified, Scalable Framework for Resume Information Extraction and Evaluation
por: Zhu, Fanwei, et al.
Publicado: (2025)

Teaching LLMs According to Their Aptitude: Adaptive Reasoning for Mathematical Problem Solving
por: Xu, Xin, et al.
Publicado: (2025)

Improved Evidence Extraction and Metrics for Document Inconsistency Detection with LLMs
por: Tan, Nelvin, et al.
Publicado: (2026)

Problem-Solving Logic Guided Curriculum In-Context Learning for LLMs Complex Reasoning
por: Ma, Xuetao, et al.
Publicado: (2025)

Graph-Augmented Relation Extraction Model with LLMs-Generated Support Document
por: Dong, Vicky, et al.
Publicado: (2024)

CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMs
por: Wang, Kangsheng, et al.
Publicado: (2024)

Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration
por: Pan, Yicheng, et al.
Publicado: (2025)

EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving
por: Dou, Shihan, et al.
Publicado: (2025)

GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving
por: Zhang, Jiaxin, et al.
Publicado: (2024)

LayoutLLM: Large Language Model Instruction Tuning for Visually Rich Document Understanding
por: Fujitake, Masato
Publicado: (2024)

Learning to Plan Before Answering: Self-Teaching LLMs to Learn Abstract Plans for Problem Solving
por: Zhang, Jin, et al.
Publicado: (2025)

RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems
por: Qu, Yuxiao, et al.
Publicado: (2025)

Multi-Head RAG: Solving Multi-Aspect Problems with LLMs
por: Besta, Maciej, et al.
Publicado: (2024)

Multi-Modal Data Exploration via Language Agents
por: Nooralahzadeh, Farhad, et al.
Publicado: (2024)

SAIL: Sample-Centric In-Context Learning for Document Information Extraction
por: Zhang, Jinyu, et al.
Publicado: (2024)

Lightweight Spatial Modeling for Combinatorial Information Extraction From Documents
por: Dong, Yanfei, et al.
Publicado: (2024)

Solving an Open Problem in Theoretical Physics using AI-Assisted Discovery
por: Brenner, Michael P., et al.
Publicado: (2026)

Spatial Information Integration in Small Language Models for Document Layout Generation and Classification
por: Melendez, Pablo, et al.
Publicado: (2025)

Exploring LLMs for Scientific Information Extraction Using The SciEx Framework
por: Li, Sha, et al.
Publicado: (2025)

Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs
por: Shiri, Fatemeh, et al.
Publicado: (2024)

Limitations of Large Language Models in Clinical Problem-Solving Arising from Inflexible Reasoning
por: Kim, Jonathan, et al.
Publicado: (2025)

Extract-0: A Specialized Language Model for Document Information Extraction
por: Godoy, Henrique
Publicado: (2025)

ASAG2024: A Combined Benchmark for Short Answer Grading
por: Meyer, Gérôme, et al.
Publicado: (2024)

Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
por: Zhou, Yuxuan, et al.
Publicado: (2025)

Exploring the Latest LLMs for Leaderboard Extraction
por: Kabongo, Salomon, et al.
Publicado: (2024)

Do Large Language Models have Problem-Solving Capability under Incomplete Information Scenarios?
por: Chen, Yuyan, et al.
Publicado: (2024)

Assessing the Capability of LLMs in Solving POSCOMP Questions
por: Viegas, Cayo, et al.
Publicado: (2025)

Explainable Collaborative Problem Solving Diagnosis with BERT using SHAP and its Implications for Teacher Adoption
por: Wong, Kester, et al.
Publicado: (2025)

LLMs are not Zero-Shot Reasoners for Biomedical Information Extraction
por: Nagar, Aishik, et al.
Publicado: (2024)

Beyond Words: How Large Language Models Perform in Quantitative Management Problem-Solving
por: Kuzmanko, Jonathan
Publicado: (2025)

Harnessing Multi-Agent LLMs for Complex Engineering Problem-Solving: A Framework for Senior Design Projects
por: Mushtaq, Abdullah, et al.
Publicado: (2025)

Replicating Human Social Perception in Generative AI: Evaluating the Valence-Dominance Model
por: Gurkan, Necdet, et al.
Publicado: (2025)