Encoder-Decoder

Rare Earth Juejin Tech Community

Nov 15, 2023 · Artificial Intelligence

Understanding the Transformer Architecture: Encoder, Decoder, and Attention Mechanisms

This article explains the Transformer model, comparing it with RNNs, detailing its encoder‑decoder structure, multi‑head and scaled dot‑product attention, embedding layers, feed‑forward networks, and the final linear‑softmax output, supplemented with diagrams and code examples.

Artificial IntelligenceAttentionDeep Learning

0 likes · 10 min read

Understanding the Transformer Architecture: Encoder, Decoder, and Attention Mechanisms

Sohu Tech Products

Jul 26, 2023 · Artificial Intelligence

Attention Mechanism, Transformer Architecture, and BERT: An In-Depth Overview

This article provides a comprehensive overview of the attention mechanism, its mathematical foundations, the transformer model architecture—including encoder and decoder components—and the BERT pre‑training model, detailing their principles, implementations, and applications in natural language processing.

BERTEncoder-DecoderNLP

0 likes · 13 min read

Attention Mechanism, Transformer Architecture, and BERT: An In-Depth Overview

Rare Earth Juejin Tech Community

Oct 11, 2022 · Artificial Intelligence

GANomaly: Theory and Source Code Analysis

This article explains the GANomaly model for semi‑supervised anomaly detection, detailing its generator‑encoder‑discriminator architecture, loss functions, testing phase scoring, and provides annotated PyTorch source code to help readers implement and understand the approach.

Anomaly DetectionDeep LearningEncoder-Decoder

0 likes · 15 min read

GANomaly: Theory and Source Code Analysis

Alimama Tech

Jun 22, 2022 · Artificial Intelligence

Learning Pixel-Level Distinctions for Video Highlight Detection

The Alibaba Mom Creative & Video Platform team introduces PLD‑VHD, a pixel‑level distinction learning framework that uses a 3D CNN encoder‑decoder with temporal and saliency modules to detect highlights, achieving state‑of‑the‑art results on public benchmarks and a 4,724‑video e‑commerce dataset, and boosting ad revenue through precise clipping and cropping.

Encoder-Decodercomputer visione-commerce

0 likes · 11 min read

Learning Pixel-Level Distinctions for Video Highlight Detection

Youku Technology

Apr 2, 2022 · Artificial Intelligence

Constrained Sequence-to-Tree Generation for Hierarchical Text Classification

At SIGIR 2022, the authors present a constrained Seq2Tree model that transforms hierarchical label taxonomies into preorder sequences and applies dynamic‑dictionary decoding to ensure label consistency, achieving superior hierarchical text classification performance on benchmark datasets and real‑world deployment within Alibaba Entertainment’s AI Brain.

Artificial IntelligenceEncoder-DecoderHierarchical Text Classification

0 likes · 5 min read

Constrained Sequence-to-Tree Generation for Hierarchical Text Classification

DataFunTalk

Jun 22, 2021 · Artificial Intelligence

Survey of Graph Neural Networks for Natural Language Processing

This comprehensive survey reviews the latest research on graph neural networks applied to natural language processing, covering graph construction methods, graph representation learning techniques, encoder‑decoder models, static and dynamic graph building, and discusses challenges, benchmarks, and future directions in the field.

Encoder-DecoderGraph ConstructionGraph Neural Networks

0 likes · 57 min read

Survey of Graph Neural Networks for Natural Language Processing

Cyber Elephant Tech Team

Apr 28, 2021 · Artificial Intelligence

Understanding BERT: From Encoder-Decoder to Transformer and Attention

This article explains the BERT model by first reviewing the Encoder-Decoder framework, then detailing the attention mechanism—including self-attention and multi-head attention—before describing the full Transformer architecture and finally outlining BERT’s encoder-only design, training stages, and fine-tuning applications.

AttentionBERTEncoder-Decoder

0 likes · 15 min read

Understanding BERT: From Encoder-Decoder to Transformer and Attention