Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective | Paper Citation Record

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This paper cites Token merging: Your ViT but faster.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Token merging: Your ViT but faster

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Transformer interpretability beyond attention visualization

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective R., Fan, Q., and Panda, R

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Diffrate: Differentiable compression rate for efficient vision transformers

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This paper cites Chasing sparsity in vision transformers: An end-to-end exploration, 2021 b.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Chasing sparsity in vision transformers: An end-to-end exploration, 2021 b

Reference 6

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This paper cites SparseViT : Revisiting activation sparsity for efficient high-resolution vision transformer.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective SparseViT : Revisiting activation sparsity for efficient high-resolution vision transformer

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This paper cites The stone-weierstrass theorem.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective The stone-weierstrass theorem

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This paper cites Imagenet: A large-scale hierarchical image database.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Imagenet: A large-scale hierarchical image database

Reference 9

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective An image is worth 16x16 words: Transformers for image recognition at scale

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This paper cites and Chong, E.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective and Chong, E

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Transformer in transformer

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This paper cites and Xiao, L.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective and Xiao, L

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This paper cites Learning multiple layers of features from tiny images.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Learning multiple layers of features from tiny images

Reference 20

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective EfficientFormer : Vision transformers at mobilenet speed

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This paper cites Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 22

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Mlp can be a good transformer learner

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Microsoft COCO: Common Objects in Context

Reference 24

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This paper cites TB-STC : Transposable block-wise N:M structured sparse tensor core.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective TB-STC : Transposable block-wise N:M structured sparse tensor core

Reference 25

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Swin transformer: Hierarchical vision transformer using shifted windows

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective ShortGPT : Layers in large language models are more redundant than you expect

Reference 29

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Speedup deep learning models on gpu by taking advantage of efficient unstructured pruning and bit-width reduction

Reference 30

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective DynamicViT : Efficient vision transformers with dynamic token sparsification

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective A Simple and Effective Pruning Approach for Large Language Models

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Going deeper with image transformers

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Regression analysis

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective PVT v2 : Improved baselines with pyramid vision transformer

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Joint token pruning and squeezing towards more aggressive compression of vision transformers

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective GTP-ViT : Efficient vision transformers via graph-based token propagation

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Evo-ViT : Slow-fast token evolution for dynamic vision transformer

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Global vision transformer pruning with hessian-aware saliency

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Width & depth pruning for vision transformers

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unified visual transformer compression

Reference 43

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective SAViT : Structure-aware vision transformer pruning via collaborative optimization

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Scene parsing through ade20k dataset

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Vision Transformer Pruning

Reference 47

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective IEEE Transactions on Pattern Analysis and Machine Intelligence , volume=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops , pages=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective International Conference on Machine Learning , pages=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Layer Folding: Neural Network Depth Reduction using Activation Linearization

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Langley , title=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective I , publisher=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Newell and P

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective and Kaiser,

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective International Conference on Learning Representations , year=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective International Conference on Machine Learning , year=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction Without Convolutions , year=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective MViTv2: Improved Multiscale Vision Transformers for Classification and Detection

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective and Tan, Mingxing , booktitle=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2021 , eprint=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2022 , eprint=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective DaViT: Dual Attention Vision Transformers

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective ReSTR: Convolution-free Referring Image Segmentation Using Transformers

Reference 72

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2022 , eprint=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective , title=

Reference 74

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2021 , eprint=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective International Conference on Learning Representations , year=

Reference 76

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective MLP Can Be a Good Transformer Learner , year=

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks

Reference 79

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2021 , eprint=

Reference 80

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot

Reference 81

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2024 , eprint=

Reference 82

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition

Reference 83

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective LPViT: Low-Power Semi-structured Pruning for Vision Transformers

Reference 84

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Beyond 2:4: exploring V:N:M sparsity for efficient transformer inference on GPUs

Reference 85

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

Reference 86

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2022 , eprint=

Reference 87

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

Reference 88

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the 36th International Conference on Machine Learning , series=

Reference 89

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2019 , eprint=

Reference 90

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the 36th International Conference on Neural Information Processing Systems , articleno=

Reference 91

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective ImageNet: A Large-Scale Hierarchical Image Database , year=

Reference 92

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Scene Parsing Through ADE20K Dataset , year=

Reference 93

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective TinyMIM: An Empirical Study of Distilling MIM Pre-trained Models

Reference 94

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Observation c3a68de2-506d-47a8-a342-2c3a810511f3 · outbound

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Token Merging: Your

Reference 95

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective International Conference on Machine Learning , pages=

Reference 96

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Distilling the Knowledge in a Neural Network

Reference 97

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

Reference 98

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 99

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 100

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , month=

Reference 101

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2022 , pages=

Reference 102

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , year=

Reference 103

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective PPT: Token Pruning and Pooling for Efficient Vision Transformers

Reference 104

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

Reference 105

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Proceedings of the AAAI Conference on Artificial Intelligence , author=

Reference 106

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Isomorphic Pruning for Vision Models

Reference 107

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective 2025 , organization=

Reference 108

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective Unresolved cited work

Reference 109

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Reference 110

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