The attention-based encoder-decoder (AED) speech recognition model has been widely successful in recent years. However, the joint optimization of acoustic model and language model in end-to-end manner ...

The decoder takes the context vector produced by the encoder and generates an output sequence. Key points about the decoder include: Output Generation: It processes the context vector and generates an ...

Decoder-based LLMs can be broadly classified into three main types: encoder-decoder, causal decoder, and prefix decoder. Each architecture type exhibits distinct attention patterns. Encoder-Decoder ...

Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

Quantile-Based Encoder-Decoder Deep Learning Models for Multi-Step Ahead Hydrological Forecasting [Conference presentation]. American Geophysical Union (AGU) Fall Meeting 2022, Online. Recent ...

The Mu small language model enables an AI agent to take action on hundreds of system settings. It’s now in preview for some ...

Many computational methods have been proposed to predict drug–drug interactions (DDIs), which can occur when combining drugs to treat various diseases, but most mainly utilize single-source features ...

Travel route recommendation is an important part of electronic tour guides and map applications. It aims to recommend a sequence of points of interest (POIs) to users based on their interests. The ...