Math: Dynamic programming

Rate-adaptive KV-cache quantizer

Allocate different entropy budgets to different KV-cache blocks instead of assigning every token and head the same nominal bitwidth. Use the ECASQ Lagrangian so high-variance or attention-sensitive blocks receive more codepoints, while predictable blocks collapse to fewer symbols and become highly compressible. Preserve unbiasedness per scalar or block so reconstructed keys and values have zero mean quantization error conditional on the original tensor.