Papers with prior memory frameworks
PerMemSafe: Benchmarking Implicit Personalized Safety of Long Horizon Self-Evolving Agents (2026.findings-acl)
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| Challenge: | Existing self-evolving agents have a low safety rate in long-horizon interactions . however, this reliance on context-independent safety evaluations is insufficient . |
| Approach: | They propose a framework that explicitly models personalized risk inference and memory evolution. |
| Outcome: | The proposed framework improves implicit personalized safety by 23.8% over prior frameworks while maintaining helpfulness in long-horizon interactions. |