LoopVQ: Sub 1-bit KV Cache Quantization for Looped Transformers
Compresses related key–value cache entries across loops with shared vector codes, then adjusts the codebooks to match the original model’s outputs. Implements the compressed cache in a serving system.
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.