51 citations · 107 across the 33 of their papers we have counts for
8 papers · 1 filter
Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery
Pengwei Yan, Kaisong Song, Zhuoren Jiang +4
While self-supervised graph pretraining techniques have shown promising results in various domains, their application still experiences challenges of limited topology learning, hum…
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph
Tianqianjin Lin, Kaisong Song, Zhuoren Jiang +6
Heterogeneous graph neural networks have become popular in various domains. However, their generalizability and interpretability are limited due to the discrepancy between their in…
Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration
Yiquan Wu, Siying Zhou, Yifei Liu +6
Legal Judgment Prediction (LJP) has become an increasingly crucial task in Legal AI, i.e., predicting the judgment of the case in terms of case fact description. Precedents are the…
Community-Based Hierarchical Positive-Unlabeled (PU) Model Fusion for Chronic Disease Prediction
Yang Wu, Xurui Li, Xuhong Zhang +3
Positive-Unlabeled (PU) Learning is a challenge presented by binary classification problems where there is an abundance of unlabeled data along with a small number of positive data…
Goal-Oriented Prompt Attack and Safety Evaluation for LLMs
Chengyuan Liu, Fubang Zhao, Lizhi Qing +4
Large Language Models (LLMs) presents significant priority in text understanding and generation. However, LLMs suffer from the risk of generating harmful contents especially while…
PPN: Parallel Pointer-based Network for Key Information Extraction with Complex Layouts
Kaiwen Wei, Jie Yao, Jingyuan Zhang +6
Key Information Extraction (KIE) is a challenging multimodal task that aims to extract structured value semantic entities from visually rich documents. Although significant progres…