Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
IEEE

Text Summarization Using PEGASUS Transformer Model in Machine Learning

Abstract: Extracting crucial information from lengthy documents can be a time-consuming and labor-intensive process. Automatic text summarization algorithms address this challenge by condensing ...
IEEE

Multi - Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer

Abstract: This paper studies a text classification algorithm based on an improved Transformer to improve the performance and efficiency of the model in text classification tasks. Aiming at the ...