Papers Event Extraction
“Event Extraction” 태그가 달린 논문 473편 · 필터 해제
A 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 ExtractionA Multi-Domain and Multi-Task Generative Framework with Explicit Task and Domain Conditioning for Cross-Domain Event Extraction
Event extraction aims to identify event triggers, classify event types, and extract arguments to construct structured event representations. Despite strong in-domain performance, developing models that generalize robustl…
Domain GeneralizationEvent ExtractionLA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction
Large language models show strong promise for information extraction (IE), but existing reflection-based correction methods are often misaligned with structured extraction outputs. Free-form self-reflection can flag an e…
Information ExtractionReinforcement LearningRelation ExtractionEvent ExtractionGrounded Event Extraction from SEC 8-K Filings with a Fine-Grained Taxonomy
Form 8-K filings are the primary channel through which U.S. public companies disclose material events, but the SEC item codes attached to them are coarse: a single item spans routine administrative changes and chief exec…
Event ExtractionEvaluation Pitfalls and Challenges in Multimedia Event Extraction
Multimedia event extraction aims to jointly identify events and their arguments across multiple modalities, such as text and images, to support more comprehensive event understanding. While recent work reports steady and…
Event ExtractionSAMA: Semantic Anchor-aligned Augmentation for Unified Low-Resource Multimodal Information Extraction
Multimodal Information Extraction (MIE)-covering tasks such as Multimodal Named Entity Recognition (MNER), Relation Extraction (MRE), and Event Extraction (MEE)-is essential for understanding multimedia content but remai…
Information ExtractionRelation ExtractionData AugmentationEvent ExtractionA Multimodal Text- and Graph-Based Approach for Open-Domain Event Extraction from Documents
Event extraction is essential for event understanding and analysis. It supports tasks such as document summarization and decision-making in emergency scenarios. However, existing event extraction approaches have limitati…
Document SummarizationEvent ExtractionEVENT5Ws: A Large Dataset for Open-Domain Event Extraction from Documents
Event extraction identifies the central aspects of events from text. It supports event understanding and analysis, which is crucial for tasks such as informed decision-making in emergencies. Therefore, it is necessary to…
Event ExtractionUsing reasoning LLMs to extract SDOH events from clinical notes
Social Determinants of Health (SDOH) refer to environmental, behavioral, and social conditions that influence how individuals live, work, and age. SDOH have a significant impact on personal health outcomes, and their sys…
Prompt EngineeringFew-Shot LearningEvent ExtractionSTIndex: A Context-Aware Multi-Dimensional Spatiotemporal Information Extraction System
Extracting structured knowledge from unstructured data still faces practical limitations: entity and event extraction pipelines remain brittle, knowledge graph construction requires costly ontology engineering, and cross…
Information ExtractionDomain GeneralizationEvent ExtractionDIAL-KG: Schema-Free Incremental Knowledge Graph Construction via Dynamic Schema Induction and Evolution-Intent Assessment
Knowledge Graphs (KGs) are foundational to applications such as search, question answering, and recommendation. Conventional knowledge graph construction methods are predominantly static, rely ing on a single-step constr…
Question AnsweringEvent ExtractionKnowledge GraphsGraph-Native Cognitive Memory for AI Agents: Formal Belief Revision Semantics for Versioned Memory Architectures
While individual components for AI agent memory exist in prior systems, their architectural synthesis and formal grounding remain underexplored. We present Kumiho, a graph-native cognitive memory architecture grounded in…
Event ExtractionCN-Buzz2Portfolio: A Chinese-Market Dataset and Benchmark for LLM-Based Macro and Sector Asset Allocation from Daily Trending Financial News
Large Language Models (LLMs) are rapidly transitioning from static Natural Language Processing (NLP) tasks including sentiment analysis and event extraction to acting as dynamic decision-making agents in complex financia…
Sentiment AnalysisEvent ExtractionECHO: Event-Centric Hypergraph Operations via Multi-Agent Collaboration for Multimedia Event Extraction
Multimedia event extraction (M2E2) aims to predict triggers, ground arguments across text and images, and then assemble them into schema-consistent event records. Recent LLM-based approaches have shown strong potential f…
Structured PredictionEvent ExtractionRMPL: Relation-aware Multi-task Progressive Learning with Stage-wise Training for Multimedia Event Extraction
Multimedia Event Extraction (MEE) aims to identify events and their arguments from documents that contain both text and images. It requires grounding event semantics across different modalities. Progress in MEE is limite…
Relation ExtractionEvent ExtractionAgentic Workflow Using RBA$_θ$ for Event Prediction
Wind power ramp events are difficult to forecast due to strong variability, multi-scale dynamics, and site-specific meteorological effects. This paper proposes an event-first, frequency-aware forecasting paradigm that di…
Event ExtractionEvent Extraction in Large Language Model
Large language models (LLMs) and multimodal LLMs are changing event extraction (EE): prompting and generation can often produce structured outputs in zero shot or few shot settings. Yet LLM based pipelines face deploymen…
Event ExtractionEvaluating LLMs for Zeolite Synthesis Event Extraction (ZSEE): A Systematic Analysis of Prompting Strategies
Extracting structured information from zeolite synthesis experimental procedures is critical for materials discovery, yet existing methods have not systematically evaluated Large Language Models (LLMs) for this domain-sp…
Information ExtractionEvent ExtractionSCIR: A Self-Correcting Iterative Refinement Framework for Enhanced Information Extraction Based on Schema
Although Large language Model (LLM)-powered information extraction (IE) systems have shown impressive capabilities, current fine-tuning paradigms face two major limitations: high training costs and difficulties in aligni…
Information ExtractionRelation ExtractionEvent ExtractionExtracting Events Like Code: A Multi-Agent Programming Framework for Zero-Shot Event Extraction
Zero-shot event extraction (ZSEE) remains a significant challenge for large language models (LLMs) due to the need for complex reasoning and domain-specific understanding. Direct prompting often yields incomplete or stru…
Event ExtractionCode Generation