Controlled Memory Interference in Continual LLM Agents
Uncovering how memory conflicts and interference shape the long-term reliability of autonomous AI agents.
Long-term memory enables AI agents to maintain continuity across sessions, personalize behavior, and evolve through accumulated experience. Yet memory evolution is not simply a process of storing more information: new experiences may reinforce, revise, or interfere with existing ...
ArXiv CS.AI
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Controlled Memory Interference reveals that agent memory evolution is hampered by conflicting information, not just storage capacity limits. This research establishes a vital framework for building more resilient, interference-aware systems that can reliably update knowledge without corrupting previous experiences.
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