Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-running agent's workspace outgrows its context window long before the task finishes. The first approach commonly used, compaction, loses the fine-grained execution evidence. And text retrieval re-prefills content the model already processed. KVMem keeps the overflow as paged KV state instead, spread across GPU memory, host memory and NVMe. Lightweight…