{"total":31,"rows":[{"id":"2305.05003","title":"Revisiting Relation Extraction in the era of Large Language Models","created":"2023-05-08","cited_by_count":102,"area":null},{"id":"2205.12696","title":"Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction","created":"2022-05-25","cited_by_count":57,"area":null},{"id":"2204.01098","title":"A sequence-to-sequence approach for document-level relation extraction","created":"2022-04-03","cited_by_count":25,"area":null},{"id":"2304.10996","title":"BERT Based Clinical Knowledge Extraction for Biomedical Knowledge Graph Construction and Analysis","created":"2023-04-21","cited_by_count":18,"area":null},{"id":"2401.13598","title":"Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet Extraction","created":"2024-01-24","cited_by_count":14,"area":null},{"id":"2410.04752","title":"Document-level Causal Relation Extraction with Knowledge-guided Binary Question Answering","created":"2024-10-07","cited_by_count":12,"area":null},{"id":"2305.03642","title":"Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs","created":"2023-05-05","cited_by_count":10,"area":null},{"id":"2310.15743","title":"RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extraction","created":"2023-10-24","cited_by_count":9,"area":null},{"id":"2305.03960","title":"Beyond Rule-based Named Entity Recognition and Relation Extraction for Process Model Generation from Natural Language Text","created":"2023-05-06","cited_by_count":8,"area":null},{"id":"2408.13889","title":"LLM with Relation Classifier for Document-Level Relation Extraction","created":"2024-08-25","cited_by_count":8,"area":null},{"id":"2305.11029","title":"Uncertainty Guided Label Denoising for Document-level Distant Relation Extraction","created":"2023-05-18","cited_by_count":7,"area":null},{"id":"2203.05325","title":"AIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First -- Using Relation Extraction to Identify Entities","created":"2022-03-10","cited_by_count":5,"area":null},{"id":"2302.08571","title":"A Comprehensive Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniques","created":"2023-02-16","cited_by_count":4,"area":null},{"id":"2304.00824","title":"Towards Integration of Discriminability and Robustness for Document-Level Relation Extraction","created":"2023-04-03","cited_by_count":4,"area":null},{"id":"2304.01344","title":"End-to-End Models for Chemical-Protein Interaction Extraction: Better Tokenization and Span-Based Pipeline Strategies","created":"2023-04-03","cited_by_count":4,"area":null},{"id":"2306.08953","title":"Rethinking Document-Level Relation Extraction: A Reality Check","created":"2023-06-15","cited_by_count":4,"area":null},{"id":"2409.13738","title":"NLP4PBM: A Systematic Review on Process Extraction using Natural Language Processing with Rule-based, Machine and Deep Learning Methods","created":"2024-09-10","cited_by_count":3,"area":null},{"id":"2509.18901","title":"Extractive Fact Decomposition for Interpretable Natural Language Inference in one Forward Pass","created":"2025-09-23","cited_by_count":3,"area":null},{"id":"2204.12070","title":"Symlink: A New Dataset for Scientific Symbol-Description Linking","created":"2022-04-26","cited_by_count":2,"area":null},{"id":"2205.01909","title":"Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction","created":"2022-05-04","cited_by_count":2,"area":null},{"id":"2303.11141","title":"DocRED-FE: A Document-Level Fine-Grained Entity And Relation Extraction Dataset","created":"2023-03-20","cited_by_count":2,"area":null},{"id":"2310.11085","title":"Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language Models","created":"2023-10-17","cited_by_count":2,"area":null},{"id":"2404.12788","title":"REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linking","created":"2024-04-19","cited_by_count":2,"area":null},{"id":"2504.04083","title":"A Benchmark for End-to-End Zero-Shot Biomedical Relation Extraction with LLMs: Experiments with OpenAI Models","created":"2025-04-05","cited_by_count":2,"area":null},{"id":"2402.13470","title":"How Important is Domain Specificity in Language Models and Instruction Finetuning for Biomedical Relation Extraction?","created":"2024-02-21","cited_by_count":1,"area":null},{"id":"2406.07444","title":"On the Robustness of Document-Level Relation Extraction Models to Entity Name Variations","created":"2024-06-11","cited_by_count":1,"area":null},{"id":"2410.14225","title":"Few-Shot Joint Multimodal Entity-Relation Extraction via Knowledge-Enhanced Cross-modal Prompt Model","created":"2024-10-18","cited_by_count":1,"area":null},{"id":"2307.11762","title":"Similarity-based Memory Enhanced Joint Entity and Relation Extraction","created":"2023-07-14","cited_by_count":0,"area":null},{"id":"2403.18025","title":"Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NER","created":"2024-03-26","cited_by_count":0,"area":null},{"id":"2412.13503","title":"VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level Relation Extraction","created":"2024-12-18","cited_by_count":0,"area":null},{"id":"2505.09792","title":"Interim Report on Human-Guided Adaptive Hyperparameter Optimization with Multi-Fidelity Sprints","created":"2025-05-14","cited_by_count":0,"area":null}],"next_cursor":null}