ICML Paper: Training-Free LLM Scaling Prediction
burny_tech · x · 2026-07-10
Research slated for presentation at ICML 2026 proposes a method to predict the scaling capabilities of Large Language Models (LLMs) without actual training. By deriving data-limited scaling exponents from measurable language statistics (such as token correlation and next-token entropy), the approach was validated across multiple models.
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