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原文摘要

LLM agents with long-term memory store conversations as short notes that later models read. A note can turn progressive "I am working at Corvida" into simple-present "The user works at Corvida," dropping the cue that the job may be temporary and that the stored fact may go stale. We call this aspectual flattening and measure it with LAPSE, a benchmark of matched user statements that differ only in temporal form. Three writer models flattened the progressive statement but kept its simple-present match in 210 of 381 pairs, never the reverse. This one-way loss held in all 11 models tested and in the agent memory systems mem0, Graphiti, and Letta. In exploratory tests, reader models judged a fact less likely to still hold when only its stored verb was progressive. In a planned test, the reader GLM-5.2 acted without asking the user on 64% of "works" notes but 40% of "is working" notes. Gemini 3 Flash showed a smaller gap, one reader added later showed the reverse, and others showed none. In a further exploratory test, free-text notes erased this difference and notes that kept the user's words restored it. Agent memory systems should keep the user's wording as evidence for later readers.