To fill this gap, we propose two attention-mechanism-based encoder–decoder models that incorporate multisource ... cross-attention mechanism, and graph attention network to construct a multisource ...

A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users.

each line is a json object whose keys are "seq", "g_ids", "g_id_features", "g_adj": "seq" is a text which is supposed to be the output of the decoder "g_ids" is a ...

The third key component of Hi-GMAE is the Fine- and Coarse-Grained (Fi-Co) encoder and decoder. The hierarchical encoder integrates fine-grained graph convolution modules to capture local information ...

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...

Abstract: Vision-based action segmentation is an important tool in human movement analysis. In this work, we present a novel Encoder-Decoder Graph Convolutional Network (ED-GCN) to perform ...

In the late 1930s, Claude Shannon showed that by using switches that close for "true" and open for "false," it was possible to carry out logical operations by assigning the number 1 to "true" and 0 ...

Hello. First of all, I'm not good at English, so please understand me. i want to transform weights of monodepth2 to onnx. so I wrote codes. This model is divided into two parts, encoder and decoder.