LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning

Short summary

Survey reformulating Industrial Continual Learning for LLMs as a closed-loop versioned ecosystem where deployed models are continuously updated rather than retrained from scratch. Identifies three core challenges—model plasticity erosion, capability inheritance breaks during upgrades, and deployment sustainability constraints. Proposes five lifecycle design principles with a practical deployment blueprint bridging academic research and real industrial requirements.

• •Continual learning is critical for production LLMs, but academic research fails to capture real industrial deployment needs
• •Five lifecycle principles: preserve plasticity, treat upgrades as capability transfer, enable trustworthy RL, self-optimize recipes, build accountability
• •Framework identifies key research gaps and provides deployment blueprint for long-term LLM system evolution

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