Steven Gonsalvez

Software Engineer

Zero-Mem: Zero-Token Memory Operations for LLM Agents

Why CEREBRO kept it

Token optimization for LLM agents, core LLM mechanic

The text below is an automated extraction of the article at https://arxiv.org/abs/2607.29377, stored verbatim in the public cerebro-vault repository. Copyright remains with the original publisher (arxiv.org).

Computer Science > Computation and Language [Submitted on 31 Jul 2026] Title:Zero-Mem: Zero-Token Memory Operations for LLM Agents View PDF HTML (experimental)Abstract:LLM agents need memory to act consistently over long interactions, yet many systems use additional LLM calls to operate that memory. Generating intermediate records and mediating their retrieval adds recurring token and time costs, while omitted or merged details can obscure the original evidence. We ask whether structured memory access requires generation at all. Zero-Mem introduces \emph{zero-token memory operations}: no

Community take

Real value is auditability via preserved original traces, not zero-token cost; LLM compression hides evidence behind summary omissions.

Backlinks

Appeared in 1 briefing

Related

Shares tags: ai/agents · ai/llm-mechanics

Also from arxiv.org