Poster "dynamic sparse training" Papers

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Conference

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Brain network science modelling of sparse neural networks enables Transformers and LLMs to perform as fully connected

Yingtao Zhang, Diego Cerretti, Jialin Zhao et al.

NEURIPS 2025arXiv:2501.19107
3
citations

Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness

Boqian Wu, Qiao Xiao, Shunxin Wang et al.

ICLR 2025arXiv:2410.03030
7
citations

Advancing Dynamic Sparse Training by Exploring Optimization Opportunities

Jie Ji, Gen Li, Lu Yin et al.

ICML 2024

Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency

Vithursan Thangarasa, Shreyas Saxena, Abhay Gupta et al.

ICML 2024arXiv:2303.11525
8
citations