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

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, ...

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 ...

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 ...

This repository provides an Encoder-Decoder Sequence-to-Sequence model to generate captions for input videos. Moreover, pre-Trained VGG16 model is being used to extract features for every frame of the ...

Call it the return of Clippy — this time with AI. Microsoft’s new small language model shows us the future of interfaces.

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 ...

Mu is built on a transformer-based encoder-decoder architecture featuring 330 million token parameters, making the SLM a good ...