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Paper Citation Record · LEDGER

Quick ViTs: Speeding up Vision Transformers through Equivariance

As of 20 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 4 inbound Pith citation observations for arXiv:2505.15441.

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

pith.paper-citation-record.v1
2505.15441 v5

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:25:00.131075Z

measured 73 of 73 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:27:30.763780Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T10:04:36.130406Z

Reference resolution

69 of 69 outbound references displayed

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  • unresolved30
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bbde78ef-2731-47fe-9e57-760ed0ae9bd1 · outbound

This paper cites write newline.

Quick ViTs: Speeding up Vision Transformers through Equivariance write newline

Reference 1

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Observation 01c3b81a-edba-4007-b7a7-ed4f423763aa · outbound

This paper cites @esa (Ref.

Quick ViTs: Speeding up Vision Transformers through Equivariance @esa (Ref

Reference 2

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Observation 677ab94a-43ef-422d-84ed-e67708d7dd15 · outbound

This paper cites an unresolved cited work.

Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 3

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Observation dd47ed3d-a8f4-4a56-97f0-d24e9f54e3b8 · outbound

This paper cites an unresolved cited work.

Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 4

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Observation d9986c00-5005-46c0-b8b6-ab78941d8af3 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.

Quick ViTs: Speeding up Vision Transformers through Equivariance Accurate structure prediction of biomolecular interactions with alphafold 3

Reference 5

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Observation 5a7838e7-4130-458b-9f2f-3a220c078e16 · outbound

This paper cites Getting vit in shape: Scaling laws for compute-optimal model design.

Quick ViTs: Speeding up Vision Transformers through Equivariance Getting vit in shape: Scaling laws for compute-optimal model design

Reference 6

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Observation 5d9e5b79-2b3d-4fb4-9de7-5b689d84d6ee · outbound

This paper cites Vn-transformer: Rotation-equivariant attention for vector neurons.

Quick ViTs: Speeding up Vision Transformers through Equivariance Vn-transformer: Rotation-equivariant attention for vector neurons

Reference 7

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Observation e30d4d6e-7c20-4958-b957-449c47129dab · outbound

This paper cites How to scale your model.

Quick ViTs: Speeding up Vision Transformers through Equivariance How to scale your model

Reference 8

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Observation 853b16d9-9877-40d1-a3d1-5a7bee12ea73 · outbound

This paper cites Roto-translation covariant convolutional networks for medical image analysis.

Quick ViTs: Speeding up Vision Transformers through Equivariance Roto-translation covariant convolutional networks for medical image analysis

Reference 9

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Observation b6ce0b7d-f608-49c6-b58d-40ed676c7a9f · outbound

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Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 10

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Observation 3bd2a9cf-6352-4f3a-a3ba-679f933ca5fa · outbound

This paper cites An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks

Reference 11

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Observation 34f3dbb6-4662-4648-8d25-94a0defc6851 · outbound

This paper cites o kman, David Nordstr \.

Quick ViTs: Speeding up Vision Transformers through Equivariance o kman, David Nordstr \

Reference 12

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Source-reported events for the cited work

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Observation 2cac53fe-7815-4e95-8841-3e4e8c4a564e · outbound

This paper cites Does equivariance matter at scale? Transactions on Machine Learning Research, 2025.

Quick ViTs: Speeding up Vision Transformers through Equivariance Does equivariance matter at scale? Transactions on Machine Learning Research, 2025

Reference 13

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Observation 3179e332-da79-44d7-ae34-59ca306cd42c · outbound

This paper cites Group-invariant max filtering.

Quick ViTs: Speeding up Vision Transformers through Equivariance Group-invariant max filtering

Reference 14

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Source-reported events for the cited work

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Observation 7aa98e4b-4989-41c0-a343-3e557f7e159c · outbound

This paper cites End-to-end object detection with transformers.

Quick ViTs: Speeding up Vision Transformers through Equivariance End-to-end object detection with transformers

Reference 15

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Observation ce8086ae-52f1-4286-9a59-b3c7b72b0f42 · outbound

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

Quick ViTs: Speeding up Vision Transformers through Equivariance Sparsevit: Revisiting activation sparsity for efficient high-resolution vision transformer

Reference 16

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Observation 1e440d77-a292-469b-a512-e5793cda4fdc · outbound

This paper cites Group equivariant convolutional networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance Group equivariant convolutional networks

Reference 17

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Observation fb29af2d-a095-4127-88dd-a6b53096ae57 · outbound

This paper cites Steerable CNN s.

Quick ViTs: Speeding up Vision Transformers through Equivariance Steerable CNN s

Reference 18

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Observation fafee053-559f-495d-8f85-425b7d1fcab5 · outbound

This paper cites Flash A ttention-2: Faster attention with better parallelism and work partitioning.

Quick ViTs: Speeding up Vision Transformers through Equivariance Flash A ttention-2: Faster attention with better parallelism and work partitioning

Reference 19

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Observation 440e3251-3bbc-499b-8ec0-39ab22dea2fa · outbound

This paper cites Cluster and predict latents patches for improved masked image modeling.

Quick ViTs: Speeding up Vision Transformers through Equivariance Cluster and predict latents patches for improved masked image modeling

Reference 20

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Observation b9eefcc2-4de2-4623-a72c-aa1ccccdc7cf · outbound

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Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 21

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Observation 876d975a-e885-4dd5-ba31-61240268f68b · outbound

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

Quick ViTs: Speeding up Vision Transformers through Equivariance Imagenet: A large-scale hierarchical image database

Reference 22

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Observation 3cac26f9-8337-427b-b742-5588855e3f40 · outbound

This paper cites Exploiting cyclic symmetry in convolutional neural networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance Exploiting cyclic symmetry in convolutional neural networks

Reference 23

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Observation 3932664e-0165-4365-812e-3b7ff2f61637 · outbound

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

Quick ViTs: Speeding up Vision Transformers through Equivariance An image is worth 16x16 words: Transformers for image recognition at scale

Reference 24

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Observation 04aa91e7-d192-45a7-84b4-a50db98acff9 · outbound

This paper cites RoMa: Robust Dense Feature Matching.

Quick ViTs: Speeding up Vision Transformers through Equivariance RoMa: Robust Dense Feature Matching

Reference 25

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Observation e3d38edd-e969-4d9b-a3e9-9bb93a3b8ee7 · outbound

This paper cites The pascal visual object classes (voc) challenge.

Quick ViTs: Speeding up Vision Transformers through Equivariance The pascal visual object classes (voc) challenge

Reference 26

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Observation 1969a6a1-9730-4634-8f21-c36088e40aae · outbound

This paper cites The invariantring package for macaulay2.

Quick ViTs: Speeding up Vision Transformers through Equivariance The invariantring package for macaulay2

Reference 27

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Observation 52bb86f6-0da0-484e-8b3c-94efe6cc7e44 · outbound

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Quick ViTs: Speeding up Vision Transformers through Equivariance Fuchs, Daniel E

Reference 28

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Observation c7248ed7-e4dd-44d3-8c5f-700cbdfb709d · outbound

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Quick ViTs: Speeding up Vision Transformers through Equivariance Grayson and Michael E

Reference 29

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Observation 1f6bb21c-3891-43e2-98af-3170b4c16153 · outbound

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Quick ViTs: Speeding up Vision Transformers through Equivariance Neighborhood attention transformer

Reference 30

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Observation 9bfd56da-e94f-4669-b48d-cb3aff50b498 · outbound

This paper cites Efficient equivariant network.

Quick ViTs: Speeding up Vision Transformers through Equivariance Efficient equivariant network

Reference 31

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Observation 6a0818ae-84b2-437e-8773-d6fbae098627 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Quick ViTs: Speeding up Vision Transformers through Equivariance Gaussian Error Linear Units (GELUs)

Reference 32

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Observation b9a62267-ae79-4634-9dfd-1391eb3f2cf3 · outbound

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Quick ViTs: Speeding up Vision Transformers through Equivariance Lietransformer: Equivariant self-attention for lie groups

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 984f466b-1ac3-4080-adc2-585d0ed62b35 · outbound

This paper cites Equivariance with learned canonicalization functions.

Quick ViTs: Speeding up Vision Transformers through Equivariance Equivariance with learned canonicalization functions

Reference 34

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Observation 56f99f12-68b2-4576-a86d-c15a34758035 · outbound

This paper cites The bispectrum as a source of phase-sensitive invariants for fourier descriptors: a group-theoretic approach.

Quick ViTs: Speeding up Vision Transformers through Equivariance The bispectrum as a source of phase-sensitive invariants for fourier descriptors: a group-theoretic approach

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 14716639-babc-4242-b0ce-2ef7127cd55a · outbound

This paper cites Scaling Laws for Neural Language Models.

Quick ViTs: Speeding up Vision Transformers through Equivariance Scaling Laws for Neural Language Models

Reference 36

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Observation 992a2c43-b201-43ca-b9b3-94b69edf5577 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick.

Quick ViTs: Speeding up Vision Transformers through Equivariance Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:24:59.674663Z digest=sha256:721551e21a0bcc6882d2ad8d67e63d09c05af3ba978cba3963bb3043823d4024

Observation b13db8d9-780d-4428-bf4a-cb88eed5ae65 · outbound

This paper cites Dinobloom: a foundation model for generalizable cell embeddings in hematology.

Quick ViTs: Speeding up Vision Transformers through Equivariance Dinobloom: a foundation model for generalizable cell embeddings in hematology

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.418984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:24:59.805402Z digest=sha256:1641ccec8dc6bdd41f24d451d9f179f9b34b56a4fdd41d863f1c9199914d90f0

Observation 4fd2b8d2-faef-4c0f-acb0-a4b7923fc8cf · outbound

This paper cites Steerable transformers for volumetric data.

Quick ViTs: Speeding up Vision Transformers through Equivariance Steerable transformers for volumetric data

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.410416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:24:59.960266Z digest=sha256:b49dc72276f489ca73965791b37fb47c0ec55340e9ea30f8354a10b4688d7738

Observation 3c99fe2a-704c-45f3-8ba9-8398426ff886 · outbound

This paper cites Equiformer: Equivariant graph attention transformer for 3d atomistic graphs.

Quick ViTs: Speeding up Vision Transformers through Equivariance Equiformer: Equivariant graph attention transformer for 3d atomistic graphs

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.400769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.039434Z digest=sha256:95476f3750bfe7b00cb5f818da932d42fbc45b0a8734abb510e435facf3b6553

Observation 6434e677-4eba-44c8-a1bd-26cdbff7f382 · outbound

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

Quick ViTs: Speeding up Vision Transformers through Equivariance Swin transformer: Hierarchical vision transformer using shifted windows

Reference 41

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unresolved
no resolver link, observed 2026-08-07T15:25:00.042971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.042971Z digest=sha256:432936824d965fa13cff005e1c595bf91af3a11129de5766653feb5b7d85488e

Observation 0c38a006-955e-4e62-a104-52ee698ad3c7 · outbound

This paper cites An expert-annotated dataset of bone marrow cytology in hematologic malignancies.

Quick ViTs: Speeding up Vision Transformers through Equivariance An expert-annotated dataset of bone marrow cytology in hematologic malignancies

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.046384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.046384Z digest=sha256:0b26114bff0690d7399ad6dee8aaf70a5fe15a7658ad4a4afdc9ef4cf332057c

Observation 0c84bdb6-34c5-44c7-8cf9-ec9f0075c3f4 · outbound

This paper cites cuEquivariance : High-performance equivariant neural networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance cuEquivariance : High-performance equivariant neural networks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.392412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.049897Z digest=sha256:119ef32a04861caf0d53b552264d07da836194376c406f9bf5aeec306833d77e

Observation 89a22307-641c-4434-8a60-38bf04ad771d · outbound

This paper cites an unresolved cited work.

Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.053461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.053461Z digest=sha256:40cb33901d453396adf4945f01ec2b05c1218e9a8a021dcf2023e32e815c0b2e

Observation ac162541-b0e3-4e3f-8f7c-28b5cb477e0d · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Quick ViTs: Speeding up Vision Transformers through Equivariance Pytorch: An imperative style, high-performance deep learning library

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.377262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.056620Z digest=sha256:093856a9ff70070e7c1d9e3caa0261f79d208b2ce1754de64da3620ad713e0f0

Observation 073f9b7f-a775-43eb-9dc6-a52308e6c746 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Quick ViTs: Speeding up Vision Transformers through Equivariance Learning transferable visual models from natural language supervision

Reference 46

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unresolved
no resolver link, observed 2026-08-07T15:25:00.059876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.059876Z digest=sha256:c34ec75de6f6e4a46245cfe40559e309bc8c192167698d0d625f99c55450018c

Observation 050e85e7-1670-49c7-92e1-5e08ce5ceb3a · outbound

This paper cites an unresolved cited work.

Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:25:01.360891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.063396Z digest=sha256:4e5c3da537c4b77dc5222e4017c0fc0c379f03d956604ecc144826282934fbf2

Observation b24e5e57-cf9c-42cb-9557-dbc7398c01d9 · outbound

This paper cites Rojas-Gomez, Teck-Yian Lim, Minh N.

Quick ViTs: Speeding up Vision Transformers through Equivariance Rojas-Gomez, Teck-Yian Lim, Minh N

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.351357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.066774Z digest=sha256:6dc23132e6db7e0b760ebd5e0f600ae0b76aa8b37721e168508e0811453a1e0a

Observation 04f08762-28b9-488b-9b8d-5e52f14059e6 · outbound

This paper cites Attentive group equivariant convolutional networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance Attentive group equivariant convolutional networks

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.341392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.069748Z digest=sha256:6bc0c7bfde5505000ed1702a26f3d2a3321d157e8dba676aba53616a3e007ed1

Observation 6d3dda3a-4831-4f83-9e82-0e591b75cd77 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Quick ViTs: Speeding up Vision Transformers through Equivariance Imagenet large scale visual recognition challenge

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.072822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.072822Z digest=sha256:379e5f4cdbd8ea646a4f771d0eb372b7adb3bfa6031e9867f88956e105dbff6d

Observation 0a6b075b-e5e0-4a83-b244-7f65b2a45c00 · outbound

This paper cites A general framework for robust g-invariance in g-equivariant networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance A general framework for robust g-invariance in g-equivariant networks

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.322042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.075731Z digest=sha256:848d95e0c08ac8ed4eeee11b40b129f30e38f0541bc788306a3cc37f2477ba08

Observation 488246ac-a2a3-4be3-949f-d09dc5438ff1 · outbound

This paper cites Linear Representations of Finite Groups , volume 42 of Graduate Texts in Mathematics.

Quick ViTs: Speeding up Vision Transformers through Equivariance Linear Representations of Finite Groups , volume 42 of Graduate Texts in Mathematics

Reference 52

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unresolved
no resolver link, observed 2026-08-07T15:25:00.079099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.079099Z digest=sha256:e54d2ca56d32d6837e9fd65698a83b82012f20839558c5b532f55bf446720ad9

Observation 884df359-cb9b-4099-97a2-bb9fcdf1d99c · outbound

This paper cites an unresolved cited work.

Quick ViTs: Speeding up Vision Transformers through Equivariance Unresolved cited work

Reference 53

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unresolved
no resolver link, observed 2026-08-07T15:25:00.082462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.082462Z digest=sha256:fb249c039820ac5176156f8ed40145ae9b59508f829c3531eb8b78055e3bb22c

Observation d66495ab-dae1-4aa7-a1b8-ae902b7e3261 · outbound

This paper cites Deit iii: Revenge of the vit.

Quick ViTs: Speeding up Vision Transformers through Equivariance Deit iii: Revenge of the vit

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.304235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.085422Z digest=sha256:fba6c5a57252f31e777347f595df3911df81fce961c01c88f62190882e7ca229

Observation 2080a968-4a48-4648-b484-eca3e9e4bed6 · outbound

This paper cites Probing Equivariance and Symmetry Breaking in Convolutional Networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance Probing Equivariance and Symmetry Breaking in Convolutional Networks

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.088220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.088220Z digest=sha256:23de025db83c55b0dc77b527ac1b1de7571a494ba390080f5960dacf9a230a5c

Observation 56229692-0a08-4198-b321-5ad9c8617b82 · outbound

This paper cites Benchmarking representation learning for natural world image collections.

Quick ViTs: Speeding up Vision Transformers through Equivariance Benchmarking representation learning for natural world image collections

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.289037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.091327Z digest=sha256:95d2c0d14827d599981a249b2416270324f8372264743f05572e9833f3b1e7c1

Observation 33a34b82-5c15-4afa-b7dd-7ac7cb4441a3 · outbound

This paper cites Attention is all you need.

Quick ViTs: Speeding up Vision Transformers through Equivariance Attention is all you need

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.094139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.094139Z digest=sha256:a44b620740bc8663132aaf37e7ac35dd9833eee38456929dcfda74e853fd707d

Observation 76c1902a-cd4b-4764-aa8a-9990c3e1a3c8 · outbound

This paper cites VGGT: Visual Geometry Grounded Transformer.

Quick ViTs: Speeding up Vision Transformers through Equivariance VGGT: Visual Geometry Grounded Transformer

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.097364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.097364Z digest=sha256:4a60bfd49cf075932de52a0bea1c861e8c35281794272e3b823f945ec9c72010

Observation 59d2a013-a693-4b7d-a00c-5d1c021c3818 · outbound

This paper cites Dust3r: Geometric 3d vision made easy.

Quick ViTs: Speeding up Vision Transformers through Equivariance Dust3r: Geometric 3d vision made easy

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.270335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.100816Z digest=sha256:74d0352273976c96d94206909c1a6b62eb1fb7183c1ede8b3f3230aa4117806f

Observation a564d382-238b-4913-8aa6-3ec51fdd062e · outbound

This paper cites Swallowing the bitter pill: Simplified scalable conformer generation.

Quick ViTs: Speeding up Vision Transformers through Equivariance Swallowing the bitter pill: Simplified scalable conformer generation

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.258709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.104240Z digest=sha256:5b9766fef414e5a5e8cb5199c9851ccf78ebbb348b697e669d0442623079fc4b

Observation a5cc7fec-fa18-4668-bfe9-7aca779859c0 · outbound

This paper cites General E(2) -equivariant steerable CNN s.

Quick ViTs: Speeding up Vision Transformers through Equivariance General E(2) -equivariant steerable CNN s

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.247437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.107801Z digest=sha256:09f1a9268a27d0a18208a193a298df375f2d5e6473d2243bb8eb6f3bec7892fa

Observation f7ac04d5-8ffc-4323-ac5e-3d64d2066577 · outbound

This paper cites Pytorch image models.

Quick ViTs: Speeding up Vision Transformers through Equivariance Pytorch image models

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.110748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.110748Z digest=sha256:e0de4ade33aee597929931d62e772fd978caa5f2f363aefc063c6563ecf71808

Observation a383838c-415a-463e-9136-61a4ee781e84 · outbound

This paper cites Representation theory and invariant neural networks.

Quick ViTs: Speeding up Vision Transformers through Equivariance Representation theory and invariant neural networks

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.220306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.113990Z digest=sha256:973bf26249517505ae37f0f0cc48439012b1a7fe1ac9357930346c90e0772625

Observation 5fd7f0c3-796f-4eb4-83e1-a5a9faa439aa · outbound

This paper cites Cvt: Introducing convolutions to vision transformers.

Quick ViTs: Speeding up Vision Transformers through Equivariance Cvt: Introducing convolutions to vision transformers

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.179230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.116987Z digest=sha256:5ea1bf64371d41876211d0b051f91fbccae896a8b11fefee61ab2902b6decdfe

Observation 016e0189-061c-4297-9758-3f0e6857c9bd · outbound

This paper cites e (2) -equivariant vision transformer.

Quick ViTs: Speeding up Vision Transformers through Equivariance e (2) -equivariant vision transformer

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:01.079647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.119569Z digest=sha256:ff0ae840db650de10800d1852c13085654c523a39b9cc773ab7204c38cf93ad5

Observation 02636207-895d-4df1-af95-d46b395bb7aa · outbound

This paper cites Scaling vision transformers.

Quick ViTs: Speeding up Vision Transformers through Equivariance Scaling vision transformers

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:00.823101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.122203Z digest=sha256:fe1f13386c0d8e5d3eae1384c5a37afcd0d7ecd4f8bd778dfa756d35c98ede1e

Observation ec9226b8-1929-431c-9505-6a685a337fd3 · outbound

This paper cites Places: A 10 million image database for scene recognition.

Quick ViTs: Speeding up Vision Transformers through Equivariance Places: A 10 million image database for scene recognition

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:00.632362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.124906Z digest=sha256:8528938124bf20834246cb4380bd78ec70c202854559e2b75111f76f4529535f

Observation e4308765-75f1-45f9-a154-43f8de0a3eb6 · outbound

This paper cites Scene parsing through ade20k dataset.

Quick ViTs: Speeding up Vision Transformers through Equivariance Scene parsing through ade20k dataset

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:25:00.519956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:25:00.128279Z digest=sha256:00a260cb69e6a714f5586eb582d1e65715678de35f77ddc5e422da37faeb4000

Observation 0b044900-2ae1-4dcf-866f-b74598099022 · outbound

This paper cites Semantic understanding of scenes through the ade20k dataset.

Quick ViTs: Speeding up Vision Transformers through Equivariance Semantic understanding of scenes through the ade20k dataset

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:00.131075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:00.131075Z digest=sha256:4368ec86f03a1b2c24cf9285ff4fbc19abb2487c9cfc3122614a60625bb4cf65

Pith citing papers

Observation a9be8c19-4284-4297-a167-a0398f5b1dac · inbound

Platonic Transformers: A Solid Choice For Equivariance cites this paper.

Platonic Transformers: A Solid Choice For Equivariance Quick ViTs: Speeding up Vision Transformers through Equivariance

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-04T12:27:30.763780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T12:27:30.763780Z digest=sha256:3a35658ef981ff4e5d33a2412f15e0b64edfbc27af9ffb5a6306499ca9724651

Observation 6f5e8a57-bb5f-4ff4-84a1-9bf866a8ca89 · inbound

Who Handles Orientation? Investigating Invariance in Feature Matching cites this paper.

Who Handles Orientation? Investigating Invariance in Feature Matching Quick ViTs: Speeding up Vision Transformers through Equivariance

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-07T03:18:46.986811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T15:06:13.894356Z digest=sha256:48cd8f57a0c27b0fbe89c4e7e16b3f8db321c07b3b9c0e769a8e79d25fdd61a1

Observation 959c1bd3-4cd5-41d9-bc60-2a1beea51387 · inbound

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ cites this paper.

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ Quick ViTs: Speeding up Vision Transformers through Equivariance

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-07-07T03:18:46.986811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-29T04:37:29.865733Z digest=sha256:07e9ab4551d61d3fdd8bba259a1f09374ca72cb740e445d81e6bfb7e47bcfb86

Observation 6a117b49-53d8-4dc6-863a-a1acaadf77d2 · inbound

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ cites this paper.

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ Quick ViTs: Speeding up Vision Transformers through Equivariance

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-07-07T03:18:46.986811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-30T09:59:55.032554Z digest=sha256:8b041f1d5115a6b4bf7ec6c8242fa77c9b8ccae4fe805815fe72b4c0deedce15