VitaBench: Memory Lifecycles Beyond Retrieval
Abstract
Long-term memory benchmarks for language agents primarily evaluate whether information from earlier interactions can be retrieved and used when it becomes relevant. Persistent memory systems, however, face an additional problem before future use is known: deciding how a memory should persist over time — whether it should remain exact, be compressed, consolidated, or deleted. Existing benchmarks capture long-range retrieval, temporal reasoning, evidence reuse, and incremental interaction, but generally do not directly evaluate the quality of these earlier representation decisions. We formalize this problem as memory lifecycle evaluation and introduce VitaBench, a benchmark that makes lifecycle decisions measurable through repeated memory reviews and full-horizon counterfactual evaluation. VitaBench contains a controlled Diagnostic tier that isolates distinct future-use patterns and a Naturalistic tier that composes them into generated customer-service-style interaction streams. We characterize lifecycle decision structure with three diagnostics: lifecycle headroom, which measures the advantage of adaptive representation choices over the best fixed strategy; horizon reversal, which measures when short-horizon decisions change under delayed consequences; and optimal-action diversity, which measures whether different memory states favor different lifecycle operations. Across both tiers, VitaBench exhibits substantial lifecycle structure: lifecycle headroom is 1.364 in Diagnostic and 1.405 in Naturalistic, and 60.2\% and 56.5\% of states, respectively, change their preferred action between short and full horizons. A learned delayed lifecycle policy further improves over the best fixed strategy on VitaBench-Naturalistic, reaching 101.5 versus 83.4 joint utility. These results show that retrieving past information and deciding how it should persist are distinct evaluation problems, and that lifecycle management requires evaluation of the delayed consequences of representation decisions.