Memory poisoning via lost-provenance documents in agent memory stores creates agent misconduct that safety systems misattribute to model failure; the paper defines Semantic Norm Drift, releases a benchmark, and proposes a new testing method plus a defense.
InAdvances in Neural Information Processing Systems.https://neurips.cc/virtual/2025/poster/118152 [Dubey et al.(2024)] Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, et al
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The Misattribution Gap: When Memory Poisoning Looks Like Model Failure in Agentic AI Systems
Memory poisoning via lost-provenance documents in agent memory stores creates agent misconduct that safety systems misattribute to model failure; the paper defines Semantic Norm Drift, releases a benchmark, and proposes a new testing method plus a defense.