AI

Why Bother Me Again? Benchmarking Personal Agent Memory for Interaction Preferences

Read full article at source ↗

Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 23/10/2026, 04:03:25 UTC.

Briefings

This article introduces MemPABench, an interactive environment for evaluating personal agent memory systems. It tests four memory types (Mem0, MemOS, simple RAG, File-based) against four LLM backbones using four simulated users with 14 preferences. The study spans 99 sessions over four months, revealing that retrieval-based systems fail to outperform no memory, while file-based memory improves accuracy but lacks context relevance. Current memory struggles to retrieve preferences and adapt to changes, making overriding default habits difficult.

Key points

• MemPABench is an interactive environment for on-policy evaluation of memory in personal agents, featuring four grounded simulated users with 14 preferences across work and personal contexts.
• Evaluation spans 99 sessions over four months, testing preference selection, delivered behavior, and sensitivity to context and preference change across four memory systems and four LLM backbones.

Context

Personal intelligence systems face increasing complexity, yet existing benchmarks focus on factual recall rather than interaction preferences. This study addresses the gap by introducing MemPABench to evaluate how agents learn and act on user preferences over long horizons.

Limitations

Evidence is limited to four simulated users and four LLM backbones; no additional background or external data is supplied. Results are based on a single preprint (arXiv:2610.30485v1) with no further validation or long-term follow-up data available.

Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 23/10/2026, 04:12:16 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.

View archived briefing on IPFS
bafybeig4yb4ezpdpad3nvmoegfkyon75pdi6hjwefxkjeuf7aacuoaungq