10 papers
Scalable Exact Densest P-Partite Subgraph Search in Heterogeneous Information Networks
Jiadong Xie, Jiaming Yang, Kangfei Zhao +1
Heterogeneous information networks (HINs) model typed entities and typed relations, where dense cross-type structures can reveal cohesive semantic patterns such as prolific author-…
PLACE: Prompt Learning for Attributed Community Search in Large Graphs
Shuheng Fang, Kangfei Zhao, Rener Zhang +2
In this paper, we propose PLACE (Prompt Learning for Attributed Community Search), an innovative graph prompt learning framework for ACS. Enlightened by prompt-tuning in Natural La…
Beyond Linear LLM Invocation: An Efficient and Effective Semantic Filter Paradigm
Nan Hou, Kangfei Zhao, Jiadong Xie +1
Large language models (LLMs) are increasingly used for semantic query processing over large corpora. A set of semantic operators derived from relational algebra has been proposed t…
ParaFormer: A Generalized PageRank Graph Transformer for Graph Representation Learning
Chaohao Yuan, Zhenjie Song, Ercan Engin Kuruoglu +5
Graph Transformers (GTs) have emerged as a promising graph learning tool, leveraging their all-pair connected property to effectively capture global information. To address the ove…
From Post To Personality: Harnessing LLMs for MBTI Prediction in Social Media
Tian Ma, Kaiyu Feng, Yu Rong +1
Personality prediction from social media posts is a critical task that implies diverse applications in psychology and sociology. The Myers Briggs Type Indicator (MBTI), a popular p…
A Survey of Graph Transformers: Architectures, Theories and Applications
Chaohao Yuan, Kangfei Zhao, Ercan Engin Kuruoglu +6
Graph Transformers (GTs) have demonstrated a strong capability in modeling graph structures by addressing the intrinsic limitations of graph neural networks (GNNs), such as over-sm…