TransformerFAM: Feedback Attention Leverages Working Memory
TransformerFAM integrates feedback attention into transformers, leveraging working memory to improve learning & reasoning capabilities. It uses Block Sliding Window Attention (BSWA) to efficiently attend to local & long-range dependencies.
This is a Plain English Papers summary of a research paper called TransformerFAM: Feedback attention is working memory. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview Introduces TransformerFAM, a new architecture that integrates feedback attention into the transformer model Feedback attention is proposed as a way to leverage working memory and improve the model's ability to learn and reason Key contributions include a new attention mechanism called Block Sliding Window Attention (BSWA) and experiments on vari...