LoopKV: Loop-Aware KV Cache Compression for Serving Looped Transformers
Allocates cache precision separately for each loop and layer, shares selected caches across loops, and reads low-attention values at lower precision to reduce the memory and latency of looped language models.
First public: · Added to this list: November 9, 2026
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Recurrent reasoning — Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.