Proposes a neuroscience-grounded memory architecture that makes interactions cheaper and more accurate with experience, rather than relying on expanding context windows.
April 1, 2026
Original Paper
Human-Like Lifelong Memory: A Neuroscience-Grounded Architecture for Infinite Interaction
arXiv · 2603.29023
The Takeaway
It challenges the 'infinite context' trend by demonstrating that context length degrades reasoning and instead proposes a structured, emotion-valenced memory system. This provides a blueprint for persistent, lifelong agent memory that avoids the reasoning decay and high costs associated with long-context LLMs.
From the abstract
Large language models lack persistent, structured memory for long-term interaction and context-sensitive retrieval. Expanding context windows does not solve this: recent evidence shows that context length alone degrades reasoning by up to 85% - even with perfect retrieval. We propose a bio-inspired memory framework grounded in complementary learning systems theory, cognitive behavioral therapy's belief hierarchy, dual-process cognition, and fuzzy-trace theory, organized around three principles: