Paper Citation Record · LEDGER

Rectifying Magnitude Neglect in Linear Attention

As of 8 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2507.00698.

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

pith.paper-citation-record.v1
2507.00698 v3

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:19:07.550066Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:41:00.065948Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:41:04.546346Z

Reference resolution

58 of 58 outbound references displayed

verified exact1
verified fuzzy50
unresolved7
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9145a1aa-9c0b-406e-95e8-71c0a101539d · outbound

This paper cites Dico: Revitalizing convnets for scalable and efficient diffusion modeling.arXiv preprint arXiv:2505.11196, 2025.

Rectifying Magnitude Neglect in Linear Attention Dico: Revitalizing convnets for scalable and efficient diffusion modeling.arXiv preprint arXiv:2505.11196, 2025

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38d44e7f-7066-4614-825f-8d821ab868e3 · outbound

This paper cites Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention.

Rectifying Magnitude Neglect in Linear Attention Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:00.441719Z

Source-reported events for the cited work

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Observation 9968c608-c7d6-47be-8343-780b5299197c · outbound

This paper cites Hydra attention: Efficient at- tention with many heads, 2022.

Rectifying Magnitude Neglect in Linear Attention Hydra attention: Efficient at- tention with many heads, 2022

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:20.687922Z

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Observation 7ed36598-d3f2-461b-b3b9-20f72eb0b618 · outbound

This paper cites Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction.

Rectifying Magnitude Neglect in Linear Attention Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:20.424606Z

Source-reported events for the cited work

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Observation fa2a4203-d3e1-4574-b86d-9eb975d2443e · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection.

Rectifying Magnitude Neglect in Linear Attention Cascade r-cnn: Delving into high quality object detection

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:20.182144Z

Source-reported events for the cited work

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Observation fa43ff33-8c38-49da-8320-60f96484e4ee · outbound

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

Rectifying Magnitude Neglect in Linear Attention Imagenet: A large-scale hierarchical image database

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:19.973630Z

Source-reported events for the cited work

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Observation 7cf8ae52-dbe5-49db-89af-f966ad21f599 · outbound

This paper cites Davit: Dual attention vision transformers.

Rectifying Magnitude Neglect in Linear Attention Davit: Dual attention vision transformers

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:19.712271Z

Source-reported events for the cited work

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Observation bb4d78eb-0f84-44bf-80e9-9e44d2df4bf1 · outbound

This paper cites Cswin transformer: A general vision transformer backbone with cross-shaped windows.

Rectifying Magnitude Neglect in Linear Attention Cswin transformer: A general vision transformer backbone with cross-shaped windows

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:19.442324Z

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Observation 65aeffec-e56b-43dd-9f91-dac0e8cc97c0 · outbound

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

Rectifying Magnitude Neglect in Linear Attention An image is worth 16x16 words: Transformers for image recognition at scale

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:19.212521Z

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Observation e057094e-7088-40dc-a8ea-489f3fa66b1d · outbound

This paper cites Rethinking Local Perception in Lightweight Vision Transformer.

Rectifying Magnitude Neglect in Linear Attention Rethinking Local Perception in Lightweight Vision Transformer

Reference 10

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Source-reported events for the cited work

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Observation a22cc143-f269-4b7e-abe9-9212e7770b32 · outbound

This paper cites Lightweight vision transformer with bidirectional interac- tion.

Rectifying Magnitude Neglect in Linear Attention Lightweight vision transformer with bidirectional interac- tion

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:18.985748Z

Source-reported events for the cited work

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Observation 2700f76e-44d2-4d84-84d1-7f24dab703be · outbound

This paper cites Semantic Equitable Clustering: A Simple and Effective Strategy for Clustering Vision Tokens.

Rectifying Magnitude Neglect in Linear Attention Semantic Equitable Clustering: A Simple and Effective Strategy for Clustering Vision Tokens

Reference 12

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Source-reported events for the cited work

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Observation dd8ce4a2-e34a-4cd4-a754-99260ff7a66c · outbound

This paper cites Rmt: Retentive networks meet vision trans- formers.

Rectifying Magnitude Neglect in Linear Attention Rmt: Retentive networks meet vision trans- formers

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:18.767291Z

Source-reported events for the cited work

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Observation f4bf5aa4-6466-485a-9aa9-1f84f6110415 · outbound

This paper cites Breaking the low- rank dilemma of linear attention.

Rectifying Magnitude Neglect in Linear Attention Breaking the low- rank dilemma of linear attention

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:18.460003Z

Source-reported events for the cited work

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Observation 9a6c5372-d27b-4e60-8e5e-2d47758cf7c4 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Rectifying Magnitude Neglect in Linear Attention Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 15

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Source-reported events for the cited work

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Observation d4cda541-698b-4e4f-bf3f-69729724d656 · outbound

This paper cites Sucheng ren, xingyi yang, songhua liu, xinchao wang.

Rectifying Magnitude Neglect in Linear Attention Sucheng ren, xingyi yang, songhua liu, xinchao wang

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:18.257598Z

Source-reported events for the cited work

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Observation 9284c903-2517-4e43-857b-cddf2146f3d1 · outbound

This paper cites Conformer: Convolution-augmented transformer for speech recognition.

Rectifying Magnitude Neglect in Linear Attention Conformer: Convolution-augmented transformer for speech recognition

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:18.000465Z

Source-reported events for the cited work

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Observation a7893eb1-fb75-4cce-96e9-e653bf927a00 · outbound

This paper cites Cmt: Convolutional neural networks meet vision transformers.

Rectifying Magnitude Neglect in Linear Attention Cmt: Convolutional neural networks meet vision transformers

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:17.749859Z

Source-reported events for the cited work

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Observation 67c60d44-9307-4828-ba71-d6c5f7aabbaa · outbound

This paper cites Visual Attention Network.

Rectifying Magnitude Neglect in Linear Attention Visual Attention Network

Reference 19

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Observation e7541606-79fa-4579-9eea-6b801c577aaf · outbound

This paper cites Flatten transformer: Vision transformer using fo- cused linear attention.

Rectifying Magnitude Neglect in Linear Attention Flatten transformer: Vision transformer using fo- cused linear attention

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:17.513839Z

Source-reported events for the cited work

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Observation 007fc3ef-bf38-4d84-bc0a-e954cf921f5a · outbound

This paper cites Bridging the divide: Reconsidering softmax and linear attention.

Rectifying Magnitude Neglect in Linear Attention Bridging the divide: Reconsidering softmax and linear attention

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:17.243944Z

Source-reported events for the cited work

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Observation 684443e9-324b-40bb-96d0-a1a5118711bf · outbound

This paper cites Demystify mamba in vision: A linear attention perspective.

Rectifying Magnitude Neglect in Linear Attention Demystify mamba in vision: A linear attention perspective

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:16.969851Z

Source-reported events for the cited work

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Observation c801c2d5-2229-41d7-9389-80e76bcd40eb · outbound

This paper cites Neighborhood attention transformer.

Rectifying Magnitude Neglect in Linear Attention Neighborhood attention transformer

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:16.709736Z

Source-reported events for the cited work

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Observation 6132a6b8-78b6-4d84-98ca-c6e9061e4c3b · outbound

This paper cites Global context vision transformers.

Rectifying Magnitude Neglect in Linear Attention Global context vision transformers

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:16.484518Z

Source-reported events for the cited work

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Observation a3f96d76-1092-4c26-8099-0373cc51fdfa · outbound

This paper cites Girshick.

Rectifying Magnitude Neglect in Linear Attention Girshick

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:16.200077Z

Source-reported events for the cited work

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Observation 23a6f295-8bd2-49ba-887d-44ee61239b85 · outbound

This paper cites Deep networks with stochastic depth.

Rectifying Magnitude Neglect in Linear Attention Deep networks with stochastic depth

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:15.797638Z

Source-reported events for the cited work

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Observation eb157f2a-398b-49dc-80cf-8337b3f47374 · outbound

This paper cites Vision transformer with super token sampling.

Rectifying Magnitude Neglect in Linear Attention Vision transformer with super token sampling

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:15.528219Z

Source-reported events for the cited work

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Observation f67d3941-620f-4400-8136-10affd50f8d2 · outbound

This paper cites Learning correlation structures for vision trans- formers.

Rectifying Magnitude Neglect in Linear Attention Learning correlation structures for vision trans- formers

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:15.251227Z

Source-reported events for the cited work

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Observation 747b32fa-34d5-4018-93cf-15938b610acc · outbound

This paper cites Panoptic feature pyramid networks.

Rectifying Magnitude Neglect in Linear Attention Panoptic feature pyramid networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:14.978260Z

Source-reported events for the cited work

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Observation b7474ed0-0bfd-4ee7-a734-97d8c6f4eade · outbound

This paper cites Mpvit: Multi-path vision transformer for dense pre- diction.

Rectifying Magnitude Neglect in Linear Attention Mpvit: Multi-path vision transformer for dense pre- diction

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:14.737588Z

Source-reported events for the cited work

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Observation 00c75224-7dcb-4896-a16a-95fd8e7f941d · outbound

This paper cites Uniformer: Unified transformer for efficient spatiotemporal representation learning, 2022.

Rectifying Magnitude Neglect in Linear Attention Uniformer: Unified transformer for efficient spatiotemporal representation learning, 2022

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:14.554977Z

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Observation 370dcb0a-992f-4ec2-92b6-eb0d032f82c5 · outbound

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Rectifying Magnitude Neglect in Linear Attention Unresolved cited work

Reference 32

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Observation bc29a7ee-2272-4bed-8938-379b5f8c6017 · outbound

This paper cites Girshick, and Kaim- ing He andPiotr Doll´ar.

Rectifying Magnitude Neglect in Linear Attention Girshick, and Kaim- ing He andPiotr Doll´ar

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:14.013358Z

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Observation 961398d4-db02-4e4a-8006-8932dd816ff4 · outbound

This paper cites Scale-aware modulation meet transformer.

Rectifying Magnitude Neglect in Linear Attention Scale-aware modulation meet transformer

Reference 34

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Observation c5063f46-8e80-49f1-84c8-2c2ea7781c37 · outbound

This paper cites Dynamic group transformer: A general vision transformer backbone with dynamic group attention.

Rectifying Magnitude Neglect in Linear Attention Dynamic group transformer: A general vision transformer backbone with dynamic group attention

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:13.523189Z

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Observation c8a1405d-1112-4917-a542-4acc74c8ce00 · outbound

This paper cites Vmamba: Visual state space model.

Rectifying Magnitude Neglect in Linear Attention Vmamba: Visual state space model

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:13.213638Z

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Observation 2ea23477-6179-4bab-8f5f-d7f640d6ceb5 · outbound

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

Rectifying Magnitude Neglect in Linear Attention Swin transformer: Hierarchical vision transformer using shifted windows

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:12.996651Z

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Observation ed0f7482-53f1-4818-be0b-73908df8e59f · outbound

This paper cites A convnet for the 2020s.

Rectifying Magnitude Neglect in Linear Attention A convnet for the 2020s

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:12.798816Z

Source-reported events for the cited work

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Observation 08c41705-6707-4838-b418-c4e04d07d0f8 · outbound

This paper cites Softmax-free linear transformers.

Rectifying Magnitude Neglect in Linear Attention Softmax-free linear transformers

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:12.622101Z

Source-reported events for the cited work

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Observation a8cb825d-52c0-4410-bae2-cf773d7bae30 · outbound

This paper cites Softmax-free linear transformers.

Rectifying Magnitude Neglect in Linear Attention Softmax-free linear transformers

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:12.436766Z

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Observation 5d2f906e-adc3-416b-8c83-a0fe03d8756a · outbound

This paper cites Scalable diffusion models with transformers.

Rectifying Magnitude Neglect in Linear Attention Scalable diffusion models with transformers

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:12.250065Z

Source-reported events for the cited work

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Observation 1ae02984-4b30-45a9-b9e4-356be6fa47d4 · outbound

This paper cites The devil in linear transformer.

Rectifying Magnitude Neglect in Linear Attention The devil in linear transformer

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:12.038736Z

Source-reported events for the cited work

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Observation 4ec9b00a-9116-42bb-98f2-0ea248cc993d · outbound

This paper cites Hornet: Efficient high-order spatial interactions with recursive gated convolutions.

Rectifying Magnitude Neglect in Linear Attention Hornet: Efficient high-order spatial interactions with recursive gated convolutions

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:11.801899Z

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Observation 4c3cbfe2-bad5-427f-90f9-00740b819da6 · outbound

This paper cites Efficient attention: Attention with linear complexities.

Rectifying Magnitude Neglect in Linear Attention Efficient attention: Attention with linear complexities

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:11.590939Z

Source-reported events for the cited work

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Observation cbafb45d-1ac5-4892-bdb6-17c4287cdb39 · outbound

This paper cites Multi-scale vmamba: Hierarchy in hierarchy visual state space model.

Rectifying Magnitude Neglect in Linear Attention Multi-scale vmamba: Hierarchy in hierarchy visual state space model

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:11.368213Z

Source-reported events for the cited work

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Observation 112ea903-b047-427b-b2fb-b0421cf05a9c · outbound

This paper cites Inception transformer.

Rectifying Magnitude Neglect in Linear Attention Inception transformer

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:11.191507Z

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Observation 9e6ed769-669d-4756-9258-e19244369217 · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

Rectifying Magnitude Neglect in Linear Attention Retentive Network: A Successor to Transformer for Large Language Models

Reference 47

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Source-reported events for the cited work

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Observation cf793440-fb68-4a7b-add7-e363d0329689 · outbound

This paper cites Dic: Rethinking conv3x3 de- signs in diffusion models.

Rectifying Magnitude Neglect in Linear Attention Dic: Rethinking conv3x3 de- signs in diffusion models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:10.969507Z

Source-reported events for the cited work

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Observation aef27405-4883-4441-8f30-0c521621fb38 · outbound

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

Rectifying Magnitude Neglect in Linear Attention Train- ing data-efficient image transformers & distillation through attention

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:10.746598Z

Source-reported events for the cited work

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Observation 10d85d9e-dd51-45e3-bfa6-888fc8281a32 · outbound

This paper cites Atten- tion is all you need.

Rectifying Magnitude Neglect in Linear Attention Atten- tion is all you need

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:10.401613Z

Source-reported events for the cited work

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Observation 91610bd9-c249-4dcb-9593-7a1048f6b2a6 · outbound

This paper cites Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions.

Rectifying Magnitude Neglect in Linear Attention Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:10.175152Z

Source-reported events for the cited work

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Observation 8c2d99c6-723a-4050-bc9f-2ff4e653ef68 · outbound

This paper cites Pvtv2: Improved baselines with pyramid vision transformer.

Rectifying Magnitude Neglect in Linear Attention Pvtv2: Improved baselines with pyramid vision transformer

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:09.899152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6ea09d62-6872-417b-a30b-c5eb1d3125ba · outbound

This paper cites Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions.

Rectifying Magnitude Neglect in Linear Attention Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions

Reference 53

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Observation 460d78d2-f125-446f-9093-6e1911ab5586 · outbound

This paper cites Unified perceptual parsing for scene understand- ing.

Rectifying Magnitude Neglect in Linear Attention Unified perceptual parsing for scene understand- ing

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:09.375485Z

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This paper cites Gated linear attention transformers with hardware-efficient training.

Rectifying Magnitude Neglect in Linear Attention Gated linear attention transformers with hardware-efficient training

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:09.109098Z

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This paper cites Castling-vit: Compressing self-attention via switching to- wards linear-angular attention during vision transformer in- ference.

Rectifying Magnitude Neglect in Linear Attention Castling-vit: Compressing self-attention via switching to- wards linear-angular attention during vision transformer in- ference

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:08.845820Z

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This paper cites Biformer: Vision transformer with bi-level routing attention.

Rectifying Magnitude Neglect in Linear Attention Biformer: Vision transformer with bi-level routing attention

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:08.577482Z

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This paper cites Dig: Scal- able and efficient diffusion models with gated linear atten- tion.

Rectifying Magnitude Neglect in Linear Attention Dig: Scal- able and efficient diffusion models with gated linear atten- tion

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:08.280714Z

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Pith citing papers

Observation 81d350e6-daa9-4c81-be6a-1967e5c631be · inbound

Norm$\times$Direction: Restoring the Missing Query Norm in Vision Linear Attention cites this paper.

Norm$\times$Direction: Restoring the Missing Query Norm in Vision Linear Attention Rectifying Magnitude Neglect in Linear Attention

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