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Found 5 papers, 2 papers with code
Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception
Specifically, we analyze the performance changes of different methods under different bandwidths, providing a deep insight into the performance-bandwidth trade-off issue.
Detecting Political Opinions in Tweets through Bipartite Graph Analysis: A Skip Aggregation Graph Convolution Approach
Public opinion is a crucial factor in shaping political decision-making.
DoubleH: Twitter User Stance Detection via Bipartite Graph Neural Networks
Subsequently, we propose a bipartite graph neural network model, DoubleH, which aims to better utilize homogeneous and heterogeneous information in user stance detection tasks.
Adaptive Zone-Aware Hierarchical Planner for Vision-Language Navigation
In this paper, we propose an Adaptive Zone-aware Hierarchical Planner (AZHP) to explicitly divides the navigation process into two heterogeneous phases, i. e., sub-goal setting via zone partition/selection (high-level action) and sub-goal executing (low-level action), for hierarchical planning.
Hierarchical information matters: Text classification via tree based graph neural network
Inspired by the structural entropy, we construct the coding tree of the graph by minimizing the structural entropy and propose HINT, which aims to make full use of the hierarchical information contained in the text for the task of text classification.
