Understand positional encoding without the math headache — it’s simpler than you think. #PositionalEncoding #NLP #Transformers101 Vatican Alters Birth Records for Two African Cardinals Ahead ...

Abstract: Recently, the self-attention mechanism (Transformer) has shown its advantages in various natural language processing (NLP) tasks. Since positional information is crucial to NLP tasks, the ...

Abstract: In Transformer-based hyperspectral image classification (HSIC), predefined positional encodings (PEs) are crucial for capturing the order of each input token. However, their typical ...

About This project demonstrates a basic Transformer-based text summarization model using TensorFlow and Keras. It processes a toy dataset of short articles and generates concise summaries. Key ...

2025/03: Recategorized "Structural Encoding / Postional Encoding for Graph Transformers" into "Absolute PE", "Relative PE" and "Graph Neural Networks as Structural Encoder".It is worth noting that ...