EP226: MELT Decouples AI Reasoning from Memory

Title: Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language ModelsSource: http://arxiv.org/abs/2605.07721v1Summary:This paper introduces a novel architectural primitive that decouples reasoning depth from memory consumption in looped language models, enabling constant-memory iterative reasoning. By sharing a single KV cache across loops via a learnable gating mechanism, it provides a foundational efficiency breakthrough for models performing multi-step computation in embedding space.