ArticleProceedings of the conference. Association for Computational Linguistics. Meeting2023
Revisiting Relation Extraction in the era of Large Language Models.
Article in Proceedings of the conference. Association for Computational Linguistics. Meeting, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Data extraction methods for systematic review (semi)automation: Update of a living systematic review.F1000Research · 2021Pooled it
- Reasoning, Contrastive, and In-Context Strategies for Opioid Use Stage Detection on Social Media.Proceedings of the ... Workshop on Patient-Oriented Language Processing · 2026Article
- The mosaic memory of large language models.Nature communications · 2026Article
- How important is domain-specific language model pretraining and instruction finetuning for biomedical relation extraction?Natural language processing and information systems : ... International Conference on Applications of Natural Language to Information Systems, NLDB ... revised papers. International Conference on Applications of Natural Language to Info... · 2026Article
- Using large language models for temporal relation extraction from pediatric clinical reports.JAMIA open · 2025Article
- Towards scalable and cross-lingual specialist language models for oncology.Scientific reports · 2025Article
- Reduction of supervision for biomedical knowledge discovery.BMC bioinformatics · 2025Article
- Augmenting Orbital Debris Identification with Neo4j-Enabled Graph-Based Retrieval-Augmented Generation for Multimodal Large Language Models.Sensors (Basel, Switzerland) · 2025Article
- LLM-IE: a python package for biomedical generative information extraction with large language models.JAMIA open · 2025Article
- Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models.Research square · 2025Article
- Approaches for extracting daily dosage from free-text prescription signatures in heart failure with reduced ejection fraction: a comparative study.JAMIA open · 2025Article
- Large language models can extract metadata for annotation of human neuroimaging publications.Frontiers in neuroinformatics · 2025Article
- Article
- DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2024Article
- Multi-label Sequential Sentence Classification via Large Language Model.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2024Article
- LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Integrating deep learning architectures for enhanced biomedical relation extraction: a pipeline approach.Database : the journal of biological databases and curation · 2024Article
- Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models.Proceedings of machine learning research · 2024Article
- Large Language Models and Genomics for Summarizing the Role of microRNA in Regulating mRNA Expression.Biomedicines · 2024Article
- Enhancing the coverage of SemRep using a relation classification approach.Journal of biomedical informatics · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Relation extraction (RE) is the core NLP task of inferring semantic relationships between entities from text. Standard supervised RE techniques entail training modules to tag tokens comprising entity spans and then predict the relationship between them. Recent work has instead treated the problem as a
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.