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Automatic differentiation in PyTorch , author=

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fields

cs.CV 1 cs.LG 1

years

2026 1 2018 1

verdicts

UNVERDICTED 2

representative citing papers

Dataset Distillation

cs.LG · 2018-11-27 · unverdicted · novelty 8.0

Dataset distillation creates a tiny synthetic training set that, when used with a fixed network initialization, produces models whose performance approximates that of models trained on the full original dataset.

LaplacianFormer:Rethinking Linear Attention with Laplacian Kernel

cs.CV · 2026-04-22 · unverdicted · novelty 5.0

LaplacianFormer uses a Laplacian kernel with an injective feature map and efficient approximations to achieve linear attention that preserves mid-range interactions better than Gaussian-based linear attention in vision transformers.

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Showing 2 of 2 citing papers.

  • Dataset Distillation cs.LG · 2018-11-27 · unverdicted · none · ref 45

    Dataset distillation creates a tiny synthetic training set that, when used with a fixed network initialization, produces models whose performance approximates that of models trained on the full original dataset.

  • LaplacianFormer:Rethinking Linear Attention with Laplacian Kernel cs.CV · 2026-04-22 · unverdicted · none · ref 55

    LaplacianFormer uses a Laplacian kernel with an injective feature map and efficient approximations to achieve linear attention that preserves mid-range interactions better than Gaussian-based linear attention in vision transformers.