Zero-Token Memory Operations for Large Language Model Agents

Zero-Mem introduces a method for large language model (LLM) agents to perform memory operations without generating intermediate tokens, using structured entity-context graphs and temporal hierarchies to reduce computational costs. It achieves competitive performance while eliminating LLM calls during memory operations, cutting time costs by 57.6% compared to baselines.

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