NEURIPS 2025 "transformer efficiency" Papers

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Attribution-Driven Adaptive Token Pruning for Transformers

YAOYAO YAN, Hui Yu, Weizhi Xu

NEURIPS 2025poster

Degrees of Freedom for Linear Attention: Distilling Softmax Attention with Optimal Feature Efficiency

Naoki Nishikawa, Rei Higuchi, Taiji Suzuki

NEURIPS 2025posterarXiv:2507.03340
1
citations

Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction

Jeffrey Willette, Heejun Lee, Sung Ju Hwang

NEURIPS 2025posterarXiv:2505.11254
2
citations

FlashBias: Fast Computation of Attention with Bias

Haixu Wu, Minghao Guo, Yuezhou Ma et al.

NEURIPS 2025posterarXiv:2505.12044
1
citations

Fourier Token Merging: Understanding and Capitalizing Frequency Domain for Efficient Image Generation

Jiesong Liu, Xipeng Shen

NEURIPS 2025poster

ZeroS: Zero‑Sum Linear Attention for Efficient Transformers

Jiecheng Lu, Xu Han, Yan Sun et al.

NEURIPS 2025spotlight