Resona: Using Retrieval to Improve Context Copying in Linear Recurrent Models
Resona is a framework that retrieves needed information from the input context and reinjects it into a linear recurrent language model. Based on the paper's abstract, this article examines the bottleneck in context copying, the meaning of combining retrieval with recurrence, and the evaluation, cost, and evidence that must be checked before practical adoption.