ENCODER-DECODER in Seq2Seq models is a game-changer for sequence-based tasks: 1. ... Depending on the NLP task, it's often wise to use multiple metrics for a holistic performance view.

In this assignment, you will implement an Encoder-Decoder model that takes in ALFRED instructions for an entire episode and predicts the sequence of corresponding, high-level actions and target ...

NLP Seq2seq Model with an Attentive Encoder-Decoder Architecture for Article Title Generation An attentional seq2seq encoder-decoder model trained to generate article titles based on their abstracts ...

Early detection of arrhythmias and anomalies by automatic classifiers can significantly support physicians' work. Here, we aim to develop a heartbeat classifier by applying a cutting-edge technique, ...

Text summarization plays a vital role in distilling essential information from large volumes of text. While significant progress has been made in English text summarization using deep learning ...

In an era where machines are increasingly expected to comprehend, generate, and interact with human language and sensory data, the concept of “attention” has emerged as a guiding beacon in the realm ...