Jev-Mem reportedly builds AI agent memory 6.6x faster
A user sharing the Jev-Mem paper says the proposed architecture puts a lightweight controller in charge of memory decisions, calling the language model only for final reasoning and answer writing.
TLDR
A post sharing the Jev-Mem paper describes a proposed memory architecture inspired by System-One/System-Two cognition. It reports 6.6x faster memory construction and a 36.7% reduction in query latency, with construction taking 158 seconds and average query latency dropping to 0.93 seconds. On LoCoMo, the post reports an overall score of 0.777 with an LLM judge—an 11.0% relative improvement over the strongest baseline.
