2 citations · 2 across the 7 of their papers we have counts for
7 papers
TikStance: A Multimodal and Hierarchical Dataset for Multi-target Stance Analysis in TikTok Political Conversations
Yazhi Zhang, Fuqiang Niu, Bowen Zhang
Political discourse has increasingly moved to short-video platforms, yet computational analysis of such content remains constrained by the scarcity of datasets that jointly preserv…
Geometry-Aware Spiking Graph Neural Network
Bowen Zhang, Genan Dai, Hu Huang +1
Graph Neural Networks (GNNs) have demonstrated impressive capabilities in modeling graph-structured data, while Spiking Neural Networks (SNNs) offer high energy efficiency through…
MT2-CSD: A New Dataset and Multi-Semantic Knowledge Fusion Method for Conversational Stance Detection
Fuqiang Niu, Genan Dai, Yisha Lu +4
In the realm of contemporary social media, automatic stance detection is pivotal for opinion mining, as it synthesizes and examines user perspectives on contentious topics to uncov…
C-MTCSD: A Chinese Multi-Turn Conversational Stance Detection Dataset
Fuqiang Niu, Yi Yang, Xianghua Fu +2
Stance detection has become an essential tool for analyzing public discussions on social media. Current methods face significant challenges, particularly in Chinese language proces…
Domain-invariant Representation Learning via Segment Anything Model for Blood Cell Classification
Yongcheng Li, Lingcong Cai, Ying Lu +8
Accurate classification of blood cells is of vital significance in the diagnosis of hematological disorders. However, in real-world scenarios, domain shifts caused by the variabili…
Towards Cross-Domain Single Blood Cell Image Classification via Large-Scale LoRA-based Segment Anything Model
Yongcheng Li, Lingcong Cai, Ying Lu +7
Accurate classification of blood cells plays a vital role in hematological analysis as it aids physicians in diagnosing various medical conditions. In this study, we present a nove…
A Challenge Dataset and Effective Models for Conversational Stance Detection
Fuqiang Niu, Min Yang, Ang Li +3
Previous stance detection studies typically concentrate on evaluating stances within individual instances, thereby exhibiting limitations in effectively modeling multi-party discus…