Paper Citation Record · LEDGER

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis

As of 18 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2412.19055.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.19055 v3

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T01:04:36.015575Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation 5fdc74f8-b5d4-445f-97d3-00673b752555 · outbound

This paper cites Quantifying Attention Flow in Transformers.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Quantifying Attention Flow in Transformers

Reference 1

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Observation 98b43cdd-2b9a-444e-b5ae-a5c9ef39f11f · outbound

This paper cites and Li, Y.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis and Li, Y

Reference 2

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Observation bd79c7a6-6346-4683-b06f-53bd3edc8557 · outbound

This paper cites Subgraphormer: Unifying subgraph GNN s and graph transformers via graph products.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Subgraphormer: Unifying subgraph GNN s and graph transformers via graph products

Reference 3

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Observation 055fa37f-fc1f-49c7-8667-56d6c7f77d0f · outbound

This paper cites Language models are few-shot learners.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Language models are few-shot learners

Reference 4

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Observation fa7cbabd-532c-4683-9479-3518fdcb6de8 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Emerging properties in self-supervised vision transformers

Reference 5

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Observation d0caf514-14fb-4941-aee1-5f61a0dd8acf · outbound

This paper cites Revisiting label smoothing and knowledge distillation compatibility: What was missing? In International Conference on Machine Learning, pp.\ 2890--2916.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Revisiting label smoothing and knowledge distillation compatibility: What was missing? In International Conference on Machine Learning, pp.\ 2890--2916

Reference 6

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Observation f498591a-4f5f-449e-ac26-8853a8add48a · outbound

This paper cites Transformer interpretability beyond attention visualization.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Transformer interpretability beyond attention visualization

Reference 7

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Observation 00736f39-239b-48ce-8051-da0a06c1d899 · outbound

This paper cites Dearkd: data-efficient early knowledge distillation for vision transformers.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Dearkd: data-efficient early knowledge distillation for vision transformers

Reference 8

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Observation 88479d2b-f271-4142-9599-d0689b2e4166 · outbound

This paper cites A comprehensive survey on model compression and acceleration.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis A comprehensive survey on model compression and acceleration

Reference 9

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Observation 4c0a4568-febe-489a-aa41-ba7626da88ca · outbound

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

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Imagenet: A large-scale hierarchical image database

Reference 10

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Observation f5d7404e-a4ef-41f7-b6d3-1292ae790f76 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 11

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Observation f62f1e47-cf2e-421e-847f-a5bcc4c3c8ba · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

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Observation 91123b34-90f6-4197-af5e-0a0b62235ce7 · outbound

This paper cites ScaleKD: Strong Vision Transformers Could Be Excellent Teachers.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis ScaleKD: Strong Vision Transformers Could Be Excellent Teachers

Reference 13

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SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Unresolved cited work

Reference 14

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Observation ea2b829f-5fbe-4a8e-9b04-b717c6b1dcf3 · outbound

This paper cites Transformer in transformer.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Transformer in transformer

Reference 15

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Observation cfffc763-c6fd-4f34-802a-280985dbd3b4 · outbound

This paper cites A survey on vision transformer.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis A survey on vision transformer

Reference 16

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Observation b0b9c40f-a5a4-42ae-8bfe-b08c74294862 · outbound

This paper cites Learning efficient vision transformers via fine-grained manifold distillation.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Learning efficient vision transformers via fine-grained manifold distillation

Reference 17

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Observation b3195623-1fbf-4257-a56d-b1a2cd8195a9 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Distilling the Knowledge in a Neural Network

Reference 18

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Observation 35125065-9f4e-435e-965a-3c04ec12cef7 · outbound

This paper cites Knowledge distillation from a stronger teacher.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Knowledge distillation from a stronger teacher

Reference 19

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SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Unresolved cited work

Reference 20

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Observation 12d22fa5-bdd3-4e02-98eb-edc91cf219a4 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Swin transformer: Hierarchical vision transformer using shifted windows

Reference 21

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Observation 85db9e62-ce3e-4219-913b-192700b92b33 · outbound

This paper cites K., Rawat, A.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis K., Rawat, A

Reference 22

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Observation af297c68-2005-43b3-9a24-cf42f19225df · outbound

This paper cites and Mikolajczyk, K.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis and Mikolajczyk, K

Reference 23

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Observation db3f44ac-557c-47d6-a605-73ceb2c72b0c · outbound

This paper cites Ia-red ^2 : Interpretability-aware redundancy reduction for vision transformers, 2021.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Ia-red ^2 : Interpretability-aware redundancy reduction for vision transformers, 2021

Reference 24

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Observation a717fd00-c5da-4cba-a30d-42d485e36b0b · outbound

This paper cites Relational knowledge distillation.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Relational knowledge distillation

Reference 25

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This paper cites Frequency attention for knowledge distillation.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Frequency attention for knowledge distillation

Reference 26

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Observation befd295c-a7fc-489c-a05d-58c6199327c7 · outbound

This paper cites and Lampert, C.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis and Lampert, C

Reference 27

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This paper cites Do vision transformers see like convolutional neural networks? Advances in neural information processing systems, 34: 0 12116--12128, 2021.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Do vision transformers see like convolutional neural networks? Advances in neural information processing systems, 34: 0 12116--12128, 2021

Reference 28

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Observation 35a1e67e-933f-49b7-92c7-0d1fd992e12e · outbound

This paper cites Dual Expert Distillation Network for Generalized Zero-Shot Learning.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Dual Expert Distillation Network for Generalized Zero-Shot Learning

Reference 29

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Observation 59316e39-1679-4f69-b93f-f7a0adc6a6b7 · outbound

This paper cites The role of masking for efficient supervised knowledge distillation of vision transformers.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis The role of masking for efficient supervised knowledge distillation of vision transformers

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T01:04:36.232528Z

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This paper cites Training data-efficient image transformers & distillation through attention.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Training data-efficient image transformers & distillation through attention

Reference 31

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This paper cites Going deeper with image transformers.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Going deeper with image transformers

Reference 32

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This paper cites Attention is all you need.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Attention is all you need

Reference 33

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SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Pytorch image models

Reference 34

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SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Self-supervised learning based on transformer for flow reconstruction and prediction

Reference 35

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Observation 968052c0-6225-40ef-b076-c51daf1b0eee · outbound

This paper cites Knowledge distillation via softmax regression representation learning.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Knowledge distillation via softmax regression representation learning

Reference 36

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Observation dcd52404-66eb-4d71-8383-e6b00e529509 · outbound

This paper cites From knowledge distillation to self-knowledge distillation: A unified approach with normalized loss and customized soft labels.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis From knowledge distillation to self-knowledge distillation: A unified approach with normalized loss and customized soft labels

Reference 37

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This paper cites Attentionviz: A global view of transformer attention.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Attentionviz: A global view of transformer attention

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T01:04:36.151494Z

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Observation 42458a0c-09fc-453e-b1d3-fbb7c7490d66 · outbound

This paper cites and Xiang, W.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis and Xiang, W

Reference 39

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Observation ae586ad2-08b9-49ef-93b1-919e965872f0 · outbound

This paper cites Peeling back the layers: Interpreting the storytelling of vit.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis Peeling back the layers: Interpreting the storytelling of vit

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T01:04:36.130481Z

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This paper cites S., Klein, T., and Brendel, W.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis S., Klein, T., and Brendel, W

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T01:04:36.120096Z

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Observation f3ea406a-8adf-4e0f-b70f-656558faa1f7 · outbound

This paper cites write newline.

SpectralKD: A Unified Framework for Interpreting and Distilling Vision Transformers via Spectral Analysis write newline

Reference 42

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Pith citing papers

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