4 citations · 4 across the 5 of their papers we have counts for
6 papers
RACap: Relation-Aware Prompting for Lightweight Retrieval-Augmented Image Captioning
Xiaosheng Long, Hanyu Wang, Zhentao Song +2
Recent retrieval-augmented image captioning methods incorporate external knowledge to compensate for the limitations in comprehending complex scenes. However, current approaches fa…
Dialogue-Based Multi-Dimensional Relationship Extraction from Novels
Yuchen Yan, Hanjie Zhao, Senbin Zhu +3
Relation extraction is a crucial task in natural language processing, with broad applications in knowledge graph construction and literary analysis. However, the complex context an…
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…
LaiDA: Linguistics-aware In-context Learning with Data Augmentation for Metaphor Components Identification
Hongde Liu, Chenyuan He, Feiyang Meng +2
Metaphor Components Identification (MCI) contributes to enhancing machine understanding of metaphors, thereby advancing downstream natural language processing tasks. However, the c…
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…