arxiv preprint - System 2 Attention (is something you might need too)

In this episode, we discuss System 2 Attention (is something you might need too) by Jason Weston, Sainbayar Sukhbaatar. The paper introduces System 2 Attention (S2A), an approach that improves Transformer-based Large Language Models by regenerating input contexts to focus on relevant information before processing, thereby enhancing the generation of the next token. S2A was created to address the problem of standard soft attention mechanisms that often integrate distracting information into outputs. In testing, S2A demonstrated superior performance by producing more factual, objective, and less biased responses on tasks such as question answering, math word problems, and longform content generation.