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Showing papers from LLM, Xiaohongshu Show all papers

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NeurIPS 2026SpotlightShanghai Jiao TongDataCanvasTsinghuaProject NuminaLLM, XiaohongshuLLM pretraining & scaling laws

Decomposing and Reshaping Scaling Laws through Token Learning Times

Pingjie Wang, zechenhu, Peiru Yang, Jingtao Han and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026FudanProject NuminaLLM, XiaohongshuThe Hong Kong University of ScieLLM pretraining & scaling laws

Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization

A framework maps compute budgets to optimal Mixture-of-Experts architectures via joint FLOP, active, and total parameter constraints, yielding robust scaling laws across hundreds of models with widening near-optimal flexibility at scale.

Weilin Wan, Jingtao Han, Debing Zhang, Weizhong Zhang and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 16 of 20 reviewers recommend it
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medium 9/10
strict 3/5