LeanMem routes agent memory by content type instead of one summarization pipeline, gaining up to 15.1 points

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LeanMem argues that dialogue content should be handled by compressibility, temporal dynamics, and fidelity requirement rather than pushed through one uniform summarize-and-retrieve path. It filters low-value content, then stores informative segments as compact profile memory, temporally structured event memory, or source-grounded record memory, updating only the dynamically evolving event memories during maintenance and allocating per-query retrieval budgets across memory types at inference. On LoCoMo and LongMemEval-S with GPT-4.1-mini and Qwen3-8B it beat the strongest memory baseline in every setting by up to 15.1 points, at the lowest or near-lowest construction cost, inference tokens, and latency.