RESEARCHarXiv CS.AI·4/16/2026
Numerical Instability and Chaos: Quantifying the Unpredictability of Large Language Models
This paper rigorously analyzes how numerical instability from finite precision leads to unpredictability in LLMs, a critical reliability issue in agentic workflows. It details rounding error propagation, identifying a chaotic "avalanche effect" in early layers and universal, scale-dependent chaotic behaviors.
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