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Kaplan and colleagues: scaling laws for neural language models

Contribution grade

Foundation-model research · Empirical model scaling

Reference score110,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Model-training tradeoffs could be summarized and forecast approximately within measured regimes.

Scientific scope

2020 ten-author paper, cross-entropy loss and tested model/data ranges; not universal laws of intelligence or guaranteed compute-optimality elsewhere.

Evidence

The linked sources identify this contribution and its scope. WRS has not independently reconstructed the scientific claims. These are empirical relationships for the architectures, data and loss regimes tested in the 2020 paper, not universal laws of intelligence or guarantees outside the measured ranges.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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