Original title: Will My Assistant Remember My Allergy? What Personal LLM Assistants Forget When Conversation Memory Is Compressed
Lichen Zhu, Yueqian Lin, Yiheng Wang, Yudong Liu +2 · September 2026
Personal AI assistants need to remember important details you mention, like a food allergy. Because of privacy, assistants run directly on devices where storage is tight. To save space, they use compression to throw away older parts of the conversation. Standard tests claim these systems remember critical facts easily using a 20% budget. But researchers noticed a flaw: those tests cheated by showing the AI the future question before deciding what to delete. When tested realistically without knowing the question ahead of time, an allergy mentioned in passing survived only 0--1% of the time, compared to 97% with full memory. The memory space is simply too small. Crucial personal facts require a separate, dedicated storage system.
Imagine you have a small notebook for jotting down reminders. You write down a friend's allergy, but later you need to add more notes. To fit new notes, you tear out old pages. The page with the allergy gets torn out because there isn't enough space to keep it. In this paper, the notebook is the AI's memory, and the allergy is a critical fact that gets lost because the system has to delete old information to make room for new.
Personal AI assistants for health and elder care must remember critical facts like allergies. But when memory is compressed for on-device privacy, these facts survive only 0-1% of the time. This makes current compression unsafe for safety-critical information, requiring a separate auditable store.
The paper does not implement or test the proposed auditable episodic store and asking interface. It only identifies the failure of current compression methods on a specific constructed dataset (PA-Bench). The results may not generalize to all types of personal facts or all compression policies.
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Will My Assistant Remember My Allergy? What Personal LLM Assistants Forget When Conversation Memory Is Compressed — Lichen Zhu, Yueqian Lin, Yiheng Wang et al.
Abstract licence: CC0
Explanation generated by Synthesis from the abstract — it is not the original paper. This is a preprint, so it hasn't necessarily been peer reviewed.