4 citations · 6 across the 7 of their papers we have counts for
5 papers · 1 filter
SILC-EFSA: Self-aware In-context Learning Correction for Entity-level Financial Sentiment Analysis
Senbin Zhu, Chenyuan He, Hongde Liu +6
In recent years, fine-grained sentiment analysis in finance has gained significant attention, but the scarcity of entity-level datasets remains a key challenge. To address this, we…
Identifying Speakers and Addressees of Quotations in Novels with Prompt Learning
Yuchen Yan, Hanjie Zhao, Senbin Zhu +3
Quotations in literary works, especially novels, are important to create characters, reflect character relationships, and drive plot development. Current research on quotation extr…
ZZU-NLP at SIGHAN-2024 dimABSA Task: Aspect-Based Sentiment Analysis with Coarse-to-Fine In-context Learning
Senbin Zhu, Hanjie Zhao, Xingren Wang +3
The DimABSA task requires fine-grained sentiment intensity prediction for restaurant reviews, including scores for Valence and Arousal dimensions for each Aspect Term. In this stud…
MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training
Xiaojing Du, Hanjie Zhao, Danyan Xing +2
In medical information extraction, medical Named Entity Recognition (NER) is indispensable, playing a crucial role in developing medical knowledge graphs, enhancing medical questio…
FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis
Songhua Yang, Xinke Jiang, Hanjie Zhao +3
Multi-domain aspect-based sentiment analysis (ABSA) seeks to capture fine-grained sentiment across diverse domains. While existing research narrowly focuses on single-domain applic…