Papers Information Extraction
“Information Extraction” 태그가 달린 논문 328편 · 필터 해제
VoxMem: Benchmarking Multimodal Memory in Large Audio Language Models
Spoken conversational systems must recover information from prior interactions (i.e., memory), yet relevant information in speech extends beyond what was said to who said it, how it was spoken, and what was audible, info…
Information ExtractionMomentQuant: an even more minimalist interval method with linear time complexity for time series classification
Time series data is very common in many real-world applications and in numerous domains, with increasing interest for automated information extraction using machine learning. One of these subfields is time series classif…
Time Series ClassificationInformation ExtractionAutomated Analysis Framework for Multilingual Climate-Health Literature Based on Multi-Agent Large Language Model
The rapid proliferation of interdisciplinary and multilingual scientific literature has left traditional manual analysis and single-algorithm methods plagued by low efficiency, poor scalability, and insufficient domain a…
Information ExtractionCorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases
LLMs are increasingly able to answer complex questions about enterprise-scale document collections. But evaluation is hard: companies don't want to share internal communications, and synthetic datasets have been overly s…
Information ExtractionMulti-Granularity Context-Enhanced RAG over Multimodal Knowledge Graphs
Retrieval-augmented generation (RAG) is widely used to mitigate hallucination issues in large language models (LLMs) and multimodal large language models (MLLMs). In particular, knowledge graph (KG)-based RAG leverages s…
Information ExtractionKnowledge GraphsWhen "Must" Becomes "Maybe": Constraint Weakening in LLM Agent Workflows
Large language model (LLM) agents coordinate complex tasks through multi-role and multi-stage workflows. Upstream state is repeatedly transformed into intermediate language artifacts, such as summaries, plans, tickets, m…
Information ExtractionA Scalable Cross-Domain Event Extraction System via a Unified Generative Training Framework
Event extraction is fundamental to information extraction. Prior approaches often separate event detection and argument extraction or depend on dataset-specific designs, limiting scalability and cross-domain generalizati…
Information ExtractionDomain GeneralizationEvent ExtractionIdentify, Locate, Link: End-to-End Key-Value Extraction from Document Images
Document processing pipelines traditionally cascade optical character recognition (OCR) engines with downstream models for structured information extraction, leading to multi-stage error propagation. We fine-tune SmolDoc…
Information ExtractionBEAR-Bench: A Bilingual Enterprise and Academic Reasoning Benchmark for Multimodal Models
While Multimodal Large Language Models (MLLMs) have made significant strides in visual comprehension, their ability to reason about text-dense, professional documents remains incompletely evaluated. Existing benchmarks e…
Information ExtractionEvaluating Structured Information Extraction with Open Models in a High Risk Public Sector Application
The extraction of structured information from unstructured documents represents a critical component of digital transformations in all sectors. While proprietary solutions dominate commercial applications, a rapidly grow…
Information ExtractionLAVA: Logic-Aware Validation and Augmentation Framework for Large-Scale Financial Document Auditing
Financial document validation in production, such as payroll auditing, tax compliance, and loan underwriting, demands exceptional accuracy, consistency, and reproducibility under strict enterprise constraints. In practic…
Information ExtractionA Pathway to General-Purpose Scientific AI: Multimodal Comprehension of Scientific Images
Scientific figures and tables encode essential experimental evidence, yet remain difficult for digital libraries and multimodal AI systems to retrieve and interpret. The ALD/E-ImageMiner benchmark and ICDAR 2026 Competit…
Visual Question AnsweringInformation ExtractionProbabilistic indirect models for undrained shear strength: addressing significant data missing and variability with advanced imputation and machine learning techniques
Accurate prediction of undrained shear strength (su) is crucial for geotechnical design, but is often hampered by substantial uncertainty in traditional empirical methods. This study uses the CLAY/10/7490 global database…
Information ExtractionEnhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach
Scientific named entity recognition (SciNER) plays a crucial role in information extraction and knowledge discovery from scientific texts. Recently, large language models (LLMs) have demonstrated the capacity to achieve …
Information ExtractionMulti-Task LearningEntity TypingSchema-Guided Hierarchical Information Extraction and Semantic Evaluation Using Generative AI
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 go…
Information ExtractionMameLoshnLM: Yiddish Language Model and Evaluation Benchmark
We present MameLoshnLM, the first open-source 8B-parameter language model built specifically for Yiddish. Despite Yiddish's rich textual tradition, its limited digital presence and the scarcity of reliable evaluation res…
Information ExtractionConstructCIE: A Dataset for Extracting Causal Information from Construction Accident Narratives
Construction accident narratives contain rich causal information, but the evidence is often implicit, long-span, and distributed. We introduce ConstructCIE, a manually annotated dataset for Causal Information Extraction …
Information ExtractionType predictionUnsupervised Multidomain Approaches to Named Entity Recognition with Small Datasets
This paper explores the challenges and the methodologies associated with learning quality representations in scenarios with unlabelled small or limited datasets for downstream information extraction task (Multidomain Nam…
Unsupervised Pre-trainingInformation ExtractionData AugmentationTransfer LearningSciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions
Scientific processes are often described in heterogeneous article discourse, with details needed for comparison, reproducibility, reuse, and automation dispersed across prose, tables, figures, protocols, and supplementar…
Information ExtractionKnowledge GraphsFrom Single- to Cross-Document: Benchmarking Multi-Granularity Event Analysis of Large Language Models
Event analysis is an essential and fundamental direction of information extraction, involving various event-centric tasks at different granularity of documents. While large language models (LLMs) have preliminarily achie…
Information Extraction