Enhancing stance detection through sequential weighted multi-task learning
The exponential growth of user-generated content on social media platforms, online news
outlets, and digital communication has necessitated the development of automated tools for …
outlets, and digital communication has necessitated the development of automated tools for …
SGCL: Semantic-aware Graph Contrastive Learning with Lipschitz Graph Augmentation
Graph contrastive learning (GCL) has gained increasing interest as a solution for graph
representation learning. In GCL, graph augmentation is essential to generate contrastive …
representation learning. In GCL, graph augmentation is essential to generate contrastive …
An LLM-Enabled Knowledge Elicitation and Retrieval Framework for Zero-Shot Cross-Lingual Stance Identification
Stance detection aims to identify the attitudes toward specific targets from text, which is an
important research area in text mining and social media analytics. Existing research is …
important research area in text mining and social media analytics. Existing research is …
MUSE-Net: Disentangling Multi-Periodicity for Traffic Flow Forecasting
Accurate forecasting of traffic flow plays a crucial role in building smart cities in the new era.
Previous work has achieved success in learning inherent spatial and temporal patterns of …
Previous work has achieved success in learning inherent spatial and temporal patterns of …
MG-SIN: Multigraph Sparse Interaction Network for Multitask Stance Detection
Stance detection on social media aims to identify if an individual is in support of or against a
specific target. Most existing stance detection approaches primarily rely on modeling the …
specific target. Most existing stance detection approaches primarily rely on modeling the …
Towards task-conflicts momentum-calibrated approach for multi-task learning
Multi-task learning (MTL) has succeeded in various industrial applications by utilizing
common knowledge among joint training tasks to enhance the generalization of MTL …
common knowledge among joint training tasks to enhance the generalization of MTL …
CoSD: Collaborative Stance Detection with Contrastive Heterogeneous Topic Graph Learning
Y Cheng, Q Zhang, C Shi, L Xiao, S Hao… - arXiv preprint arXiv …, 2024 - arxiv.org
Stance detection seeks to identify the viewpoints of individuals either in favor or against a
given target or a controversial topic. Current advanced neural models for stance detection …
given target or a controversial topic. Current advanced neural models for stance detection …