Document detail
ID
oai:arXiv.org:2403.09720
Topic
Computer Science - Computation and... Computer Science - Artificial Inte...Author
Sun, PingweiCategory
Computer Science
Year
2024
listing date
3/20/2024
Keywords
modelsAbstract
Accurately handling the underlying support values in sentences is crucial for understanding the speaker's tendencies, yet it poses a challenging task in natural language understanding (NLU).
In this article, we explore the potential of fine-tuning and prompt tuning in this downstream task, using the Human Value Detection 2023.
Additionally, we attempt to validate whether models can effectively solve the problem based on the knowledge acquired during the pre-training stage.
Simultaneously, our interest lies in the capabilities of large language models (LLMs) aligned with RLHF in this task, and some preliminary attempts are presented.
Sun, Pingwei, 2024, Fine-tuning vs Prompting, Can Language Models Understand Human Values?
A Novel MR Imaging Sequence of 3D-ZOOMit Real Inversion-Recovery Imaging Improves Endolymphatic Hydrops Detection in Patients with Ménière Disease
ménière disease p < detection imaging sequences 3d-zoomit 3d endolymphatic real tse reconstruction ir inversion-recovery hydrops ratio
