1 citations · 2 across the 7 of their papers we have counts for
8 papers
Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment
Huanyi Xie, Lijie Hu, Lu Yu +6
In the realm of Text-attributed Graphs (TAGs), traditional graph neural networks (GNNs) often fall short due to the complex textual information associated with each node. Recent me…
Towards Multi-dimensional Explanation Alignment for Medical Classification
Lijie Hu, Songning Lai, Wenshuo Chen +5
The lack of interpretability in the field of medical image analysis has significant ethical and legal implications. Existing interpretable methods in this domain encounter several…
Faithful Interpretation for Graph Neural Networks
Lijie Hu, Tianhao Huang, Lu Yu +3
Currently, attention mechanisms have garnered increasing attention in Graph Neural Networks (GNNs), such as Graph Attention Networks (GATs) and Graph Transformers (GTs). It is not…
Semi-supervised Concept Bottleneck Models
Lijie Hu, Tianhao Huang, Huanyi Xie +6
Concept Bottleneck Models (CBMs) have garnered increasing attention due to their ability to provide concept-based explanations for black-box deep learning models while achieving hi…
Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top
Keyuan Cheng, Muhammad Asif Ali, Shu Yang +7
Multi-hop Question Answering (MQA) under knowledge editing (KE) is a key challenge in Large Language Models (LLMs). While best-performing solutions in this domain use a plan and so…
Prompt-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression
Muhammad Asif Ali, Zhengping Li, Shu Yang +8
Large Language Models (LLMs) have shown exceptional abilities for multiple different natural language processing tasks. While prompting is a crucial tool for LLM inference, we obse…
Multi-hop Question Answering under Temporal Knowledge Editing
Keyuan Cheng, Gang Lin, Haoyang Fei +5
Multi-hop question answering (MQA) under knowledge editing (KE) has garnered significant attention in the era of large language models. However, existing models for MQA under KE ex…
MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions
Shu Yang, Muhammad Asif Ali, Lu Yu +2
The increasing significance of large models and their multi-modal variants in societal information processing has ignited debates on social safety and ethics. However, there exists…