Author

Hao Wu

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Jul 2026

SOAP, Muon, and Beyond: Pushing LLM Pretraining Scales

This work adapt and enhance preconditioned gradient methods to overcome the practical challenges of large-scale LLM pretraining and proposes algorithmic modifications including per-step QR orthogonalization and improved preconditioning strategies to enable stable training in these regimes.

Mikail Khona, Aditya Vavre, Boxiang Wang et al. · arXiv.org · 0 citations

#artificial intelligence Review Dec 2025

Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process

We propose LLM-PeerReview, an unsupervised LLM Ensemble method that selects the most ideal response from multiple LLM-generated candidates for each query, harnessing the collective wisdom of multiple models with diverse strengths. LLM-PeerReview is built on a novel, peer-review-inspired framework that offers a transpar...

Zhijun Chen, Zeyu Ji, Qianren Mao et al. · arXiv.org · 5 citations