arXiv:2302.13925
공식 코드 · Papers with Code
Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions
원문 초록
We describe our experiments for SemEval-2023 Task 4 on the identification of human values behind arguments (ValueEval). Because human values are subjective concepts which require precise definitions, we hypothesize that incorporating the definitions of human values (in the form of annotation instructions and validated survey items) during model training can yield better prediction performance. We explore this idea and show that our proposed models perform better than the challenge organizers' baselines, with improvements in macro F1 scores of up to 18%.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Survey on Prompt Tuning
A Survey on Latent Reasoning
A Survey on Vision-Language-Action Models for Autonomous Driving
From Tiny Machine Learning to Tiny Deep Learning: A Survey
A Comprehensive Survey on Continual Learning in Generative Models
A Survey on World Models Grounded in Acoustic Physical Information
토론
이 논문과 연결된 포럼 글이 아직 없습니다.