From the 1 of 4 linked papers with an AI index.
4 papers
Muse: Representation Geometry of Muon Beyond Normalized Momentum
Da Chang, Qiankun Shi, Lvgang Zhang +4
The paper investigates how the choice of matrix representation influences Muon-style optimizers, proposes the Muse family of optimizers that keep the same momentum and Newton–Schul…
On the Convergence of Muon and Beyond
Da Chang, Yongxiang Liu, Ganzhao Yuan
The Muon optimizer has demonstrated remarkable empirical success in handling matrix-structured parameters for training neural networks. However, a significant gap remains between i…
SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators
Xianglin Liu, Kai Yang, Fanli Zhou +9
The rapid advancement of deep learning is reshaping the hardware design landscape toward AI tasks, posing fundamental challenges for HPC workloads such as atomistic simulation. Her…
Calibrating and Rotating: A Unified Framework for Weight Conditioning in PEFT
Da Chang, Peng Xue, Yu Li +3
Parameter-Efficient Fine-Tuning (PEFT) methods are crucial for adapting large pre-trained models. Among these, LoRA is considered a foundational approach. Building on this, the inf…