A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth
In most decoder-only LLMs, nothing computed at the last layer of token t feeds the first layer of token t+1; positions communicate only through attention over cached keys and values. A Princeton researcher’s (Yifan Zhang) technical report, Recurrent Looped Transformer (RLT), proposes closing that loop. The decoder’s final hidden state and its layerwise sliding-window attention […]