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Research2026-06-09 · source-backed
The paper argues existing KV-cache compression either degrades quality or fails to scale, and proposes an end-to-end approach that holds up as context grows. For anyone running long-context inference where memory, not compute, is the actual constraint, this is the bottleneck that matters. Worth tracking against the practical kvcached approach in the skills section below, which attacks the same memory problem from the serving side.
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Shared entity: Scale / Shared topic / What happened next / Tension
Both cover Scale; overlapping topics (against, scale); picks up the Scale thread on 2026-06-23.
Same source domain / Shared topic / Tension
Reported by the same outlet (arxiv.org); overlapping topics (against, argu, memory); pushes against this story (against).
Reported by the same outlet (arxiv.org); overlapping topics (against, approach, attack); pushes against this story (against).
Reported by the same outlet (arxiv.org); overlapping topics (against, attack, bottleneck); pushes against this story (but).
Reported by the same outlet (arxiv.org); overlapping topics (against, attack, memory); pushes against this story (against).
Reported by the same outlet (arxiv.org); overlapping topics (against, argu, context); pushes against this story (against).
Same source domain / Shared topic / Downstream implication
Reported by the same outlet (arxiv.org); overlapping topics (against, attack, memory); traces where this leads (which means).
Same source domain / Shared topic / Tension
Reported by the same outlet (arxiv.org); overlapping topics (against, anyone, degrad); pushes against this story (against).