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Qitao Tan

2 accepted papers

2025

Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning

Qitao Tan, Jun Liu, Zheng Zhan, Caiwen Ding, Yanzhi Wang, Xiaolong Ma +3
NeurIPS 2025poster

Large language models (LLMs) excel across various tasks, but standard first-order (FO) fine-tuning demands considerable memory, significantly limiting real-world deployment. Recently, zeroth-order (ZO) optimization stood out as a promising memory-efficient training paradigm, avoiding backward passes…

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2025

Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning

Sheng Li, Qitao Tan, Yue Dai, Zhenglun Kong, Tianyu Wang, Jun Liu +5
ICLR 2025poster

Self-supervised learning (SSL) offers a compelling solution to the challenge of extensive labeled data requirements in traditional supervised learning. With the proven success of Vision Transformers (ViTs) in supervised tasks, there is increasing interest in adapting them for SSL frameworks. However…

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