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cs.CL2024
Distilling Fine-grained Sentiment Understanding from Large Language Models
Yice Zhang, Guangyu Xie, Hongling Xu +5
Fine-grained sentiment analysis (FSA) aims to extract and summarize user opinions from vast opinionated text. Recent studies demonstrate that large language models (LLMs) possess e…
cs.CL2024
DS-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis
Hongling Xu, Yice Zhang, Qianlong Wang +1
Recently developed large language models (LLMs) have presented promising new avenues to address data scarcity in low-resource scenarios. In few-shot aspect-based sentiment analysis…
cs.CL2024★ 1 cited
Improving In-Context Learning with Prediction Feedback for Sentiment Analysis
Hongling Xu, Qianlong Wang, Yice Zhang +4
Large language models (LLMs) have achieved promising results in sentiment analysis through the in-context learning (ICL) paradigm. However, their ability to distinguish subtle sent…