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yudasong.github.io

yudasong.github.io is Code, Models. It is ranked #2547 on the AI Radar, in AI research, first seen 6 days ago and shared in 1 post (39.1k views).

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What yudasong.github.io says about itself

A unified likelihood formulation for foundation-model training, and empirical findings on data composition, compute allocation, retention, and continual learning.

Unified Training — Training Foundation Models with a Single Algorithm Skip to article Training Foundation Models with a Single Algorithm Yuda Song 1,*,† Alvin Zhang 2,* Fahim Tajwar 1,* Daman Arora 1 Jeff Schneider 1 Daniel Khashabi 2 Ruslan Salakhutdinov 1 J. Andrew Bagnell 1,3,‡ Aarti Singh 1,‡ Andrea Zanette 1,‡ 1 Carnegie Mellon University 2 Johns Hopkins University 3 Aurora Innovation * Equal contribution † Project lead ‡ Equal advising Illustrative data schedules Pretraining data Midtraining data RL generations Best observed performance Play Restart Training progress 2.15 × 10¹⁹ FLOPs Training complete Staged training uses data…

What people said about yudasong.github.io on X

New work on Training Foundation Models with a Single Algorithm: Paper: https://arxiv.org/abs/2610.40564 Code, Models: https://yudasong.github.io/unified-training/ This work introduces Unified Training, a framework that unifies pretraining, midtraining, supervised fine-tuning and RL under a single maximum-likelihood…

— @rsalakhu, 6 days ago · 597 likes · see the post

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FAQ

What is yudasong.github.io?

Code, Models It was first shared on X 6 days ago and is ranked #2547 on the AI Radar.

Is yudasong.github.io free?

It is open source.

Who shared yudasong.github.io?

1 account on X, including @rsalakhu, in 1 post totalling 39.1k views.

Every post is read and classified by AGK Intelligence: what it is, which market it belongs to, and whether the link is a real tool. 65.6k posts from 5k X accounts over the last 14 days, 10.4k tools, 19 markets. New posts are collected several times an hour and the full ranking is recomputed every hour — last update 2026-11-06 15:10 UTC. Full method.