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20202026
most citedGetting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment

1 citations · 2 across the 13 of their papers we have counts for

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math.OC2025

Federated Learning on Riemannian Manifolds: A Gradient-Free Projection-Based Approach

Hongye Wang, Zhaoye Pan, Chang He +2

Federated learning (FL) has emerged as a powerful paradigm for collaborative model training across distributed clients while preserving data privacy. However, existing FL algorithm…

math.OC2025

On Relatively Smooth Optimization over Riemannian Manifolds

Chang He, Jiaxiang Li, Bo Jiang +2

We study optimization over Riemannian embedded submanifolds, where the objective function is relatively smooth in the ambient Euclidean space. Such problems have broad applications…