Papers Relation Classification
“Relation Classification” 태그가 달린 논문 476편 · 필터 해제
CRAFT: LLM-Based Iterative Refinement for Temporal Reasoning over Clinical Narratives
Understanding the temporal progression of symptoms in clinical narratives is critical for disease monitoring, safety surveillance, and causality assessment. Clinical narratives, however, rarely provide explicit temporal …
Relation ClassificationSEER: A Self-Grounded Evidence Interface for Controlled Spatial Relation Classification
Spatial relation questions require a model to identify the queried subject and object before comparing their layout. Yet a VLM can recognize both entities and still answer from the wrong instance or an ambiguous global v…
Relation ClassificationReversing Arrows in Large Language Models
Large language models (LLMs) have achieved strong performance on text-to-knowledge graph generation and related tasks. Nevertheless, it is still unclear whether they accurately model the direction-dependent semantics of …
Relation ClassificationGraph GenerationLightweight Person-Place Relation Extraction from Historical Newspapers with Dependency Graphs and Proximity Features
The HIPE-2026 shared task introduces person-place relation extraction from multilingual historical newspapers as a new evaluation track, classifying the at and isAt relations between pre-annotated person and location men…
Relation ClassificationRelation ExtractionCross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian
Relation extraction (RE) for low-resource languages is typically constrained by the lack of annotated corpora. We investigate the feasibility of cross-lingual RE for Romanian by combining automatic dataset translation wi…
Relation ClassificationRelation ExtractionBCL: Bayesian In-Context Learning Framework for Information Extraction
Existing information extraction (IE) tasks increasingly adopt in-context learning (ICL) with large language models. However, current approaches either show inconsistent performance across model scales or lack systematic …
Relation ClassificationInformation ExtractionWhen Better Codebooks Are Not Enough: Predictive Performance and Behavioral Reliability in LLM Political Event Coding
High accuracy does not necessarily make an LLM a faithful coder. This issue matters because many social-science studies rely on expert-written codebooks to turn text into structured data. We study this problem in politic…
Relation ClassificationSAVER: Selective As-Needed Vision Evidence for Multimodal Information Extraction
Multimodal IE in social media is difficult because a post may attach multiple images that are weakly related, redundant, or even misleading with respect to the text. In this setting, always-on multimodal fusion wastes co…
Relation ClassificationInformation ExtractionRelation ExtractionEntity TypingDiscoExplorer: An Open Interface for the Study of Multilingual Discourse Relations
The relations connecting propositions in discourse such as cause (A because B) or concession (A although B) are a subject of intense interest in Computational Linguistics and Pragmatics, but challenging to study and comp…
Relation ClassificationDifferentially Private De-identification of Dutch Clinical Notes: A Comparative Evaluation
Protecting patient privacy in clinical narratives is essential for enabling secondary use of healthcare data under regulations such as GDPR and HIPAA. While manual de-identification remains the gold standard, it is costl…
Relation ClassificationTracing Relational Knowledge Recall in Large Language Models
We study how large language models recall relational knowledge during text generation, with a focus on identifying latent representations suitable for relation classification via linear probes. Prior work shows how atten…
Relation ClassificationText GenerationFrequency-guided Multi-level Reasoning for Scene Graph Generation in Video
Video Scene Graph Generation aims to obtain structured semantic representations of objects and their relationships in videos for high-level understanding. However, existing methods still have limitations in handling long…
Video scene graph generationRelation ClassificationArgument Mining as a Text-to-Text Generation Task
Argument Mining(AM) aims to uncover the argumentative structures within a text. Previous methods require several subtasks, such as span identification, component classification, and relation classification. Consequently,…
Component ClassificationRelation ClassificationText GenerationArgument MiningClaimFlow: Tracing the Evolution of Scientific Claims in NLP
Scientific papers advance $\textit{claims}$ that later work supports, extends, or sometimes refutes. Yet existing methods for citation and claim analysis capture only fragments of this dialogue. In this work, we make the…
Relation ClassificationMultilingual Extraction and Recognition of Implicit Discourse Relations in Speech and Text
Implicit discourse relation classification is a challenging task, as it requires inferring meaning from context. While contextual cues can be distributed across modalities and vary across languages, they are not always c…
Relation ClassificationCross-Lingual TransferPrometheus Mind: Retrofitting Memory to Frozen Language Models
Adding memory to pretrained language models typically requires architectural changes or weight modification. We present Prometheus Mind, which retrofits memory to a frozen Qwen3-4B using 11 modular adapters (530MB, 7% ov…
Relation ClassificationVERHallu: Evaluating and Mitigating Event Relation Hallucination in Video Large Language Models
Video Large Language Models (VideoLLMs) exhibit various types of hallucinations. Existing research has primarily focused on hallucinations involving the presence of events, objects, and scenes in videos, while largely ne…
Relation ClassificationQuestion AnsweringRelation Extraction Capabilities of LLMs on Clinical Text: A Bilingual Evaluation for English and Turkish
The scarcity of annotated datasets for clinical information extraction in non-English languages hinders the evaluation of large language model (LLM)-based methods developed primarily in English. In this study, we present…
Relation ClassificationInformation ExtractionContrastive LearningRelation ExtractionBeDiscovER: The Benchmark of Discourse Understanding in the Era of Reasoning Language Models
We introduce BeDiscovER (Benchmark of Discourse Understanding in the Era of Reasoning Language Models), an up-to-date, comprehensive suite for evaluating the discourse-level knowledge of modern LLMs. BeDiscovER compiles …
Temporal Relation ExtractionRelation ClassificationDiscourse ParsingLink prediction Graph Neural Networks for structure recognition of Handwritten Mathematical Expressions
We propose a Graph Neural Network (GNN)-based approach for Handwritten Mathematical Expression (HME) recognition by modeling HMEs as graphs, where nodes represent symbols and edges capture spatial dependencies. A deep BL…
Relation ClassificationGraph Neural NetworkLink Prediction