Performs a multi-head attention operation (for more info, see Attention is all you need). Exactly one Query, Key and Value tensor must be present, whether or not they're stacked. For example, if StackedQueryKey is provided, both the Query and Key tensors must be null, since they're...
The Graph Attention Network (GAT) is a type of graph neural network (GNN) that uses attention mechanisms to weigh the importance of nodes’ neighbors, demonstrating flexibility and power in representation learning. However, GAT and its variants still face common challenges in GNNs, such as over-...
Usually, the credibility of news is context-dependent, and the interactions between features in contextual information are important to fake news detection. Self-attention is used to capture the informative interactions between features in contextual information. In our case, the self-attention process ...
Keywords: Fake news detection · Contextual information · Multi-head self-attention 1 Introduction In recent years, social media has provided great convenience to the public because of it's more timely and more easier to share and discuss across various social media platforms. However, social ...
Specifically, we divided the graph pooling problem into three main units: node clustering assignment, coarsened graph construction, and self-supervised mutual information module. First, to overcome the inability of simple neural network models to discriminate important nodes, a multihead attention ...
sarcasm detection; self-attention; interpretability; social media analysis1. Introduction Sarcasm is a rhetorical way of expressing dislike or negative emotions using exaggerated language constructs. It is an assortment of mockery and false politeness to intensify hostility without explicitly doing so. In...
sarcasm detection; self-attention; interpretability; social media analysis1. Introduction Sarcasm is a rhetorical way of expressing dislike or negative emotions using exaggerated language constructs. It is an assortment of mockery and false politeness to intensify hostility without explicitly doing so. In...
Finally, we use the output of multi-head interactive attention to do a pooling splicing operation as the feature vector for sentiment prediction. Next, we will introduce the various components of the AEGCN model. Figure 1. Overview of the proposed model for aspect-based sentiment classification....
Second, we present a multi-head attention mechanism to capture the words in the text that are significantly related to long space and encoding dependencies, which adds a different focus to the information outputted from the hidden layers of BiLSTM. Finally, a global average pooling is applied ...
hyperspectral image; image classification; deep learning; spectral-coordinate attention; long-range dependency1. Introduction Hyperspectral image (HSI) classification is a hot topic in the field of remote sensing. HSIs, captured by airborne visible/infrared imaging spectrometer (AVIRIS), provide rich ...