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Found 7 papers, 5 papers with code
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs
Then, we propose a simple and effective framework called Graph Chain-of-thought (Graph-CoT) to augment LLMs with graphs by encouraging LLMs to reason on the graph iteratively.
Mining Weighted Sequential Patterns in Incremental Uncertain Databases
Several algorithms exist to mine frequent patterns and weighted sequences from incremental databases.
Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approach
From an extensive experiment on both an open domain and a technical domain QA dataset, we find that our model outperforms the state-of-the-art models on various textual and factual metrics for the LFQA task.
Node Embedding using Mutual Information and Self-Supervision based Bi-level Aggregation
Graph Neural Networks (GNNs) learn low dimensional representations of nodes by aggregating information from their neighborhood in graphs.
Structure-Aware Hierarchical Graph Pooling using Information Bottleneck
Graph pooling is an essential ingredient of Graph Neural Networks (GNNs) in graph classification and regression tasks.
Unified Spatio-Temporal Modeling for Traffic Forecasting using Graph Neural Network
However, most state-of-the-art approaches have designed spatial-only (e. g. Graph Neural Networks) and temporal-only (e. g. Recurrent Neural Networks) modules to separately extract spatial and temporal features.
SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network
Most of the recent works employed graph neural networks(GNN) with multiple layers to capture the spatial dependency.
