8 papers
Harnessing Multiple Large Language Models: A Survey on LLM Ensemble
Zhijun Chen, Xiaodong Lu, Jingzheng Li +12
LLM Ensemble -- which involves the comprehensive use of multiple large language models (LLMs), each aimed at handling user queries during downstream inference, to benefit from thei…
LIVE: Learnable Monotonic Vertex Embedding for Efficient Exact Subgraph Matching (Technical Report)
Yutong Ye, Weilong Ren, Yang Liu +5
Exact subgraph matching is a fundamental graph operator that supports many graph analytics tasks, yet it remains computationally challenging due to its NP-completeness. Recent lear…
NanoNet: Parameter-Efficient Learning with Label-Scarce Supervision for Lightweight Text Mining Model
Qianren Mao, Yashuo Luo, Ziqi Qin +12
The lightweight semi-supervised learning (LSL) strategy provides an effective approach of conserving labeled samples and minimizing model inference costs. Prior research has effect…
Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary Environments
Qingyun Sun, Jiayi Luo, Haonan Yuan +4
Graph neural networks have shown remarkable success in exploiting the spatial and temporal patterns on dynamic graphs. However, existing GNNs exhibit poor generalization ability un…
Robust Graph Condensation via Classification Complexity Mitigation
Jiayi Luo, Qingyun Sun, Beining Yang +5
Graph condensation (GC) has gained significant attention for its ability to synthesize smaller yet informative graphs. However, existing studies often overlook the robustness of GC…
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
Haonan Yuan, Qingyun Sun, Junhua Shi +4
Inspired by the remarkable success of foundation models in language and vision, Graph Foundation Models (GFMs) hold significant promise for broad applicability across diverse graph…