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[ARTICLE · art-157622] src=arxiv.org ↗ pub= topic=ai-agents verified=true sentiment=↑ positive

SPECMEM: Accelerating Agentic Tool Calling via Live Memory Management

SpecMem, a live tool-call memory system described in arXiv paper 2610.31840v1, holds a 27% higher mean accepted-token rate than a frozen draft store for speculative decoding of tool calls, with gains of 11% to 34% across benchmarks and up to 1.74x wall-clock speedup. Tested on multi-session, multi-user query streams served by three open-weight models, SpecMem writes verified calls back online into bounded per-user stores with LRU eviction and defers irreversible calls behind a side-effect gate until verification confirms. Ablations attribute nearly all of the gain to keeping the store live, while per-user scoping closes a measured cross-user leakage channel and side-effect gating eliminates irreversible mistakes.

by read1 min views5 publishedOct 26, 2026

arXiv:2610.31840v1 Announce Type: new Abstract: Tool-calling agents are mostly optimized for accuracy; in deployment, however, their growing cost is latency: every tool call is decoded autoregressively. Speculative decoding accelerates this without changing the output, and retrieved past calls make strong drafts under real use, where each user's behavior tends to repeat. Yet existing systems keep no cross-session memory, or build the draft store once and never update it. We propose SpecMem, a tool-call memory kept alive and managed throughout deployment: verified calls are written back online into bounded per-user stores with LRU eviction, and a side-effect gate defers irreversible calls until verification confirms. On multi-session, multi-user query streams served by three open-weight models, a frozen store steadily loses acceptance while SpecMem holds it: a 27% gap in mean accepted tokens (+11% to +34% across benchmarks, tracking how much novel work arrives after the store is built) and up to 1.74x wall-clock speedup. Ablations attribute the gain almost entirely to keeping the store live; local per-user scoping adds no acceptance but closes a measured cross-user leakage channel, and gating on declared side effects, rather than on retrieval confidence, is what eliminates irreversible mistakes.

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