The encoder processes the input text, tokenized into sequences, and encodes it into a fixed-size context vector. It uses a stack of LSTM layers to capture the dependencies between words in the input ...

This project is a text summarization tool built entirely from scratch using an LSTM-based encoder-decoder architecture. While it has been trained on a toy dataset and is limited in performance, it is ...

Although text-to-image models excellently create realistic images from text, they struggle with long-form text due to token limits in the pretrained text encoder. In this paper, we propose the Padding ...

Text processing has a crucial role to perform in today’s information era for interpreting data and uncovering valuable insights. In this context, sentiment analysis is especially critical for ...