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Mao Xu

2 accepted papers

2026

Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings

ICML 2026poster

In this paper, we provide a comprehensive convergence analysis for the Lion optimizer. First, we establish that the original Lion achieves a convergence rate of $\mathcal{O}(d^{1/2}T^{-1/4})$, where $d$ denotes the problem dimension and $T$ is the iteration number. To improve this rate, we propose a…

Cited by 0SourceScholar
2024

To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO

ICML 2024poster

The temperature parameter plays a profound role during training and/or inference with large foundation models (LFMs) such as large language models (LLMs) and CLIP models. Particularly, it adjusts the logits in the softmax function in LLMs, which is crucial for next token generation, and it scales th…