University of Michigan - Ann Arbor

In hybrid-attention architectures, standard attention layers store Key-Value (KV) cache entries across a radix prefix tree, but recurrent layers compress past context into an evolving recurrent state that cannot be partially sliced or reused. A semantic-aware state cache maintains a compact pool of recurrent-state checkpoints attached directly to corresponding nodes of the prefix tree. When an agentic request arrives with modified context, the runtime restores recurrent state from the deepest checkpoint whose prefix position remains valid after prompt editing. Checkpoint slots within this pool are independently managed and recycled via Least Recently Used (LRU) eviction, operating separately from the main KV cache pool.

Semantic-Aware State Cache

Checkpoint slots within the semantic-aware state cache pool are independently managed and recycled via ___ eviction.

When an agentic request arrives with a modified prompt, which recurrent-state checkpoint does the runtime restore?

Semantic anchor checkpointing is the process of placing recurrent-state checkpoints specifically at special-token boundaries that denote semantic units, such as thinking blocks, tool calls and returns, and conversation turn transitions. Because agent harnesses systematically truncate or modify conversation history at these precise block boundaries—such as stripping past thinking segments or eliding older tool observations—checkpoints placed at arbitrary token offsets are routinely invalidated. By aligning checkpoints with semantic anchors, the unedited prefix cleanly terminates at a valid checkpoint, enabling full-attention layers to reuse their KV cache up to the boundary while recurrent layers resume directly from the saved anchor state, requiring re-prefill only for the new suffix.

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