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4 results for “scaling laws”

SPIN Processed News Frame: The Hype

What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs

Researchers introduce a new Capability-Driven Multimodal Scaling Law that predicts vision-language model (VLM) performance from textual capability scores of LLM backbones, enabling principled backbone selection without full training.

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arXiv Computation and Language

Aug 4, 2026

SPIN Processed News Frame: The Cushion

How to Allocate Your Tokens? Scaling Laws with Training Steps and Batch Size

Researchers introduce a 'three-term' scaling law that separates training data into steps and batch size to improve robustness and reduce required training runs for AI model scaling predictions.

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arXiv Machine Learning

Published Jul 3, 2026 · Analyzed Jul 6, 2026

SPIN Processed News Frame: The Hype

From Approximation to Emergence: A Theory of Deep Learning

A new arXiv monograph proposes a unified theoretical framework for deep learning, positioning emergence—not just approximation—as the central organizing principle of modern AI theory.

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arXiv Machine Learning

Published Jul 3, 2026 · Analyzed Jul 6, 2026

SPIN Processed News Frame: The Hype

Import AI 452: Scaling laws for cyberwar; rising tides of AI automation; and a puzzle over gDP forecasting

Import AI newsletter discusses AI research and its implications.

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Import AI

Published Apr 6, 2026 · Analyzed Jul 5, 2026