18 citations · 48 across the 11 of their papers we have counts for
12 papers
RMSL: Weakly-Supervised Insider Threat Detection with Robust Multi-sphere Learning
Yang Wang, Yaxin Zhao, Xinyu Jiao +4
Insider threat detection aims to identify malicious user behavior by analyzing logs that record user interactions. Due to the lack of fine-grained behavior-level annotations, detec…
Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales
Xinyu Yang, Yu Sun, Xinyang Chen +2
Spatial-temporal data collected across different geographic locations often suffer from missing values, posing challenges to data analysis. Existing methods primarily leverage fixe…
Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation
Tianhao Huang, Xuan Pan, Xiangrui Cai +2
Next Point-of-Interests (POIs) recommendation task aims to provide a dynamic ranking of POIs based on users' current check-in trajectories. The recommendation performance of this t…
LAN: Learning Adaptive Neighbors for Real-Time Insider Threat Detection
Xiangrui Cai, Yang Wang, Sihan Xu +4
Enterprises and organizations are faced with potential threats from insider employees that may lead to serious consequences. Previous studies on insider threat detection (ITD) main…
AoM: Detecting Aspect-oriented Information for Multimodal Aspect-Based Sentiment Analysis
Ru Zhou, Wenya Guo, Xumeng Liu +3
Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspects from text-image pairs and recognize their sentiments. Existing methods make great efforts to align the wh…
From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment
Yu Zhao, Yike Wu, Xiangrui Cai +3
Entity Alignment (EA) aims to find the equivalent entities between two Knowledge Graphs (KGs). Existing methods usually encode the triples of entities as embeddings and learn to al…
BadPrompt: Backdoor Attacks on Continuous Prompts
Xiangrui Cai, Haidong Xu, Sihan Xu +2
The prompt-based learning paradigm has gained much research attention recently. It has achieved state-of-the-art performance on several NLP tasks, especially in the few-shot scenar…
MoSE: Modality Split and Ensemble for Multimodal Knowledge Graph Completion
Yu Zhao, Xiangrui Cai, Yike Wu +4
Multimodal knowledge graph completion (MKGC) aims to predict missing entities in MKGs. Previous works usually share relation representation across modalities. This results in mutua…
Overcoming Language Priors in Visual Question Answering via Distinguishing Superficially Similar Instances
Yike Wu, Yu Zhao, Shiwan Zhao +4
Despite the great progress of Visual Question Answering (VQA), current VQA models heavily rely on the superficial correlation between the question type and its corresponding freque…
Multi-grained Label Refinement Network with Dependency Structures for Joint Intent Detection and Slot Filling
Baohang Zhou, Ying Zhang, Xuhui Sui +2
Slot filling and intent detection are two fundamental tasks in the field of natural language understanding. Due to the strong correlation between these two tasks, previous studies…
Improving Captioning for Low-Resource Languages by Cycle Consistency
Yike Wu, Shiwan Zhao, Jia Chen +3
Improving the captioning performance on low-resource languages by leveraging English caption datasets has received increasing research interest in recent years. Existing works main…
Medical Concept Embedding with Time-Aware Attention
Xiangrui Cai, Jinyang Gao, Kee Yuan Ngiam +3
Embeddings of medical concepts such as medication, procedure and diagnosis codes in Electronic Medical Records (EMRs) are central to healthcare analytics. Previous work on medical…