arXiv:2212.07219
VTCC-NLP at NL4Opt competition subtask 1: An Ensemble Pre-trained language models for Named Entity Recognition
원문 초록
We propose a combined three pre-trained language models (XLM-R, BART, and DeBERTa-V3) as an empower of contextualized embedding for named entity recognition. Our model achieves a 92.9% F1 score on the test set and ranks 5th on the leaderboard at NL4Opt competition subtask 1.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Medical Spoken Named Entity Recognition
Software Mention Recognition with a Three-Stage Framework Based on BERTology Models at SOMD 2024
Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
Label-Guided In-Context Learning for Named Entity Recognition
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's Zibaldone
A Comparative Analysis of Static Word Embeddings for Hungarian
토론
이 논문과 연결된 포럼 글이 아직 없습니다.