"The Surprising Effectiveness of Shared Memory in Looped Transformers" Each loop for looped transformers still maintains its own KV cache, which leads to a growing memory. This paper introduces Looped Prediction Transformers, where the first loop builds a shared KV cache, while later loops reuse it and keep only a small local window. Surprisingly, sharing memory also improves model quality. At five loops, the hybrid model achieves lower perplexity and higher downstream accuracy than a…