3 papers
cs.CL2024
RNG: Reducing Multi-level Noise and Multi-grained Semantic Gap for Joint Multimodal Aspect-Sentiment Analysis
Yaxin Liu, Yan Zhou, Ziming Li +4
As an important multimodal sentiment analysis task, Joint Multimodal Aspect-Sentiment Analysis (JMASA), aiming to jointly extract aspect terms and their associated sentiment polari…
cs.CL2024
A Novel Prompt-tuning Method: Incorporating Scenario-specific Concepts into a Verbalizer
Yong Ma, Senlin Luo, Yu-Ming Shang +2
The verbalizer, which serves to map label words to class labels, is an essential component of prompt-tuning. In this paper, we present a novel approach to constructing verbalizers.…
cs.CL2024
Enhancing Source Code Classification Effectiveness via Prompt Learning Incorporating Knowledge Features
Yong Ma, Senlin Luo, Yu-Ming Shang +2
Researchers have investigated the potential of leveraging pre-trained language models, such as CodeBERT, to enhance source code-related tasks. Previous methodologies have relied on…