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Found 6 papers, 3 papers with code
LIST: Learning to Index Spatio-Textual Data for Embedding based Spatial Keyword Queries
With the proliferation of spatio-textual data, Top-k KNN spatial keyword queries (TkQs), which return a list of objects based on a ranking function that considers both spatial and textual relevance, have found many real-life applications.
Should We Respect LLMs? A Cross-Lingual Study on the Influence of Prompt Politeness on LLM Performance
We investigate the impact of politeness levels in prompts on the performance of large language models (LLMs).
Graph Attention Multi-Layer Perceptron
Graph neural networks (GNNs) have achieved great success in many graph-based applications.
Ranked #12 on
Node Property Prediction
on ogbn-mag
Model Degradation Hinders Deep Graph Neural Networks
Graph Neural Networks (GNNs) have achieved great success in various graph mining tasks. However, drastic performance degradation is always observed when a GNN is stacked with many layers.
GRAND+: Scalable Graph Random Neural Networks
In this work, we present a scalable and high-performance GNN framework GRAND+ for semi-supervised graph learning.
Ranked #1 on
Node Classification
on MAG-scholar-C
Graph Attention MLP with Reliable Label Utilization
Graph neural networks (GNNs) have recently achieved state-of-the-art performance in many graph-based applications.
