A large-scale evaluation across multiple benchmarks and model backbones found that many dedicated agent memory systems underperform naive retrieval-augmented generation (RAG) on long-horizon tasks, according to the study "Memory Tax: Dissecting the Net Value of Agent Memory." The research questions the net value of building memory over direct retrieval from raw history, a gap the authors say remains largely unclear despite memory's growing use in long-horizon agents.
Memory is increasingly used in long-horizon agents, yet the net value of building memory over direct retrieval from raw history remains largely unclear. Through a large-scale evaluation across multiple benchmarks and model backbones, we find many dedicated memory systems underperform naive RAG in ma
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