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Paper Citation Record · LEDGER

MLP-Mixer: An all-MLP Architecture for Vision

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2105.01601.

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

pith.paper-citation-record.v1
2105.01601 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:32:52.309122Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

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External citation measurements

1445
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 118767e3-ce2a-4ce9-8a48-50bd3c354ec5 · inbound

Efficiently Modeling Long Sequences with Structured State Spaces cites this paper.

Efficiently Modeling Long Sequences with Structured State Spaces MLP-Mixer: An all-MLP Architecture for Vision

Reference 41

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arxiv_id, observed 2026-05-11T10:41:55.808830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-11T10:41:55.618357Z digest=sha256:3bd352cf6f39a0aa9926f5a5dcb2d9fd9475069c77a194de156231a5f1f6f129

Observation 9436486f-6b20-4dba-8496-366e33a11e65 · inbound

RWKV: Reinventing RNNs for the Transformer Era cites this paper.

RWKV: Reinventing RNNs for the Transformer Era MLP-Mixer: An all-MLP Architecture for Vision

Reference 14

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arxiv_id, observed 2026-05-13T10:53:42.079952Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation aecdae05-5999-4a21-ae6d-72d63d8560ea · inbound

Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making cites this paper.

Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making MLP-Mixer: An all-MLP Architecture for Vision

Reference 20

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Observation e05ef0ac-1274-4421-8a77-801e2b43a443 · inbound

CV-Cities: Advancing Cross-View Geo-Localization in Global Cities cites this paper.

CV-Cities: Advancing Cross-View Geo-Localization in Global Cities MLP-Mixer: An all-MLP Architecture for Vision

Reference 7

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source=pdf_text observed=2026-08-12T17:36:34.084916Z digest=sha256:0b3ded3a3a79905078f647cdc019c14bbf83d49f30f9774ccc63c16f90ad0576

Observation 8a3c28e8-d1b0-4420-a206-8fbbe184f929 · inbound

Dual-Representation Interaction Driven Image Quality Assessment with Restoration Assistance cites this paper.

Dual-Representation Interaction Driven Image Quality Assessment with Restoration Assistance MLP-Mixer: An all-MLP Architecture for Vision

Reference 45

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source=pdf_text observed=2026-08-12T12:12:45.385963Z digest=sha256:aef2925476529e1f29a17a703ab4fac65cb60ce7c7e6e4688a28d6b70858551e

Observation cefcc746-cada-43a7-b3c0-6257b017d033 · inbound

ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts cites this paper.

ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts MLP-Mixer: An all-MLP Architecture for Vision

Reference 60

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no resolver link, observed 2026-08-11T17:59:15.744703Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:15.744703Z digest=sha256:1236b6de4f31dfef2ba281ec8c2d53178367199349aa08b85f7b8e9d86a4e71b

Observation 03a491d0-fdb0-4e89-9e8f-aa29dff04439 · inbound

RecConv: Efficient Recursive Convolutions for Multi-Frequency Representations cites this paper.

RecConv: Efficient Recursive Convolutions for Multi-Frequency Representations MLP-Mixer: An all-MLP Architecture for Vision

Reference 70

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Observation fc07db14-ae42-420c-96e5-09893689eb72 · inbound

Relative Layer-Wise Relevance Propagation: a more Robust Neural Networks eXplaination cites this paper.

Relative Layer-Wise Relevance Propagation: a more Robust Neural Networks eXplaination MLP-Mixer: An all-MLP Architecture for Vision

Reference 38

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source=pdf_text observed=2026-08-10T15:20:09.965791Z digest=sha256:4dd78543c674822b1d5db1e6a9c327208a4cb7ceb7b0cfcf7881394065ac8981

Observation 974178f5-6108-4571-a00c-db671ef4042b · inbound

QuantBench: Benchmarking AI Methods for Quantitative Investment cites this paper.

QuantBench: Benchmarking AI Methods for Quantitative Investment MLP-Mixer: An all-MLP Architecture for Vision

Reference 29

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Observation 56723980-c304-46d2-8959-20c18b51060a · inbound

Unsupervised 2D-3D lifting of non-rigid objects using local constraints cites this paper.

Unsupervised 2D-3D lifting of non-rigid objects using local constraints MLP-Mixer: An all-MLP Architecture for Vision

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T06:05:05.528423Z digest=sha256:222b5e2963d12c30200bcbe3cd4a01788b54f42114e6d3f7cdecd5d0e4194279

Observation 2a2ac725-4e2f-4ca5-9db3-93e2c7a3cef6 · inbound

TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs cites this paper.

TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs MLP-Mixer: An all-MLP Architecture for Vision

Reference 38

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no resolver link, observed 2026-08-07T14:15:46.972275Z

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source=pdf_text observed=2026-08-07T14:15:46.972275Z digest=sha256:b1e0340ed924d5a6e9c249a7c9725c175091c90e40e89117251595526ca0d551

Observation ea28c7a0-18af-4086-bfbc-242b9042ad46 · inbound

Knowledge Distillation for Reservoir-based Classifier: Human Activity Recognition cites this paper.

Knowledge Distillation for Reservoir-based Classifier: Human Activity Recognition MLP-Mixer: An all-MLP Architecture for Vision

Reference 27

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source=pdf_text observed=2026-08-07T13:01:33.436568Z digest=sha256:165088af047ddb28805773cc42d36e7f3e80bb9e0bb1a9f5056710cae19bbfa1

Observation 3dfdcaae-078a-49e3-af05-5a8ca0f587e5 · inbound

AllTracker: Efficient Dense Point Tracking at High Resolution cites this paper.

AllTracker: Efficient Dense Point Tracking at High Resolution MLP-Mixer: An all-MLP Architecture for Vision

Reference 48

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source=pdf_text observed=2026-08-07T05:42:15.846285Z digest=sha256:74a552f23517afbc817d1922474fd6c049a3195931408be6821e1ef31f9340cc

Observation 709b67a1-b440-4e7f-b7b2-17337238a707 · inbound

Graph-Based Deep Learning for Component Segmentation of Maize Plants cites this paper.

Graph-Based Deep Learning for Component Segmentation of Maize Plants MLP-Mixer: An all-MLP Architecture for Vision

Reference 31

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source=pdf_text observed=2026-08-06T21:25:52.324196Z digest=sha256:3c240460bb424573117269842caafe6f78fdc00ecec9df92ad643fb8de5bc202

Observation 64edded1-bd3c-49d7-bdd3-84dc1a0354dd · inbound

FW-GAN: Frequency-Driven Handwriting Synthesis with Wave-Modulated MLP Generator cites this paper.

FW-GAN: Frequency-Driven Handwriting Synthesis with Wave-Modulated MLP Generator MLP-Mixer: An all-MLP Architecture for Vision

Reference 28

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no resolver link, observed 2026-08-05T14:41:43.820076Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:41:43.820076Z digest=sha256:0c0637e7f6ed41e67af94b2f5ef5054bbec20bfdc708c42f081a66d9ab09cb0a

Observation ce65e83b-2686-4df4-b7ee-c9e96e3c4a8d · inbound

SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks cites this paper.

SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks MLP-Mixer: An all-MLP Architecture for Vision

Reference 28

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arxiv_id, observed 2026-05-10T00:14:46.480950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T00:13:15.180285Z digest=sha256:a6c79c948472cc109e9172106def26a65e5c04a8c0db2757d3eb6413177c6066

Observation 0ede220e-7df3-4f68-a3ed-135e7f591143 · inbound

Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models cites this paper.

Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models MLP-Mixer: An all-MLP Architecture for Vision

Reference 59

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arxiv_id, observed 2026-05-11T04:45:56.262520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 70ed285c-a411-4d90-8934-145363dd5746 · inbound

Understanding Asynchronous Inference Methods for Vision-Language-Action Models cites this paper.

Understanding Asynchronous Inference Methods for Vision-Language-Action Models MLP-Mixer: An all-MLP Architecture for Vision

Reference 18

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arxiv_id, observed 2026-05-12T01:46:13.801618Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 3446ebc4-7b4c-4587-b6be-88d0ec3d18b2 · inbound

The Chandra-Gaia Catalog of Counterparts: Resolving ambiguous Gaia matches to X-ray sources in the Chandra Source Catalog using Machine Learning cites this paper.

The Chandra-Gaia Catalog of Counterparts: Resolving ambiguous Gaia matches to X-ray sources in the Chandra Source Catalog using Machine Learning MLP-Mixer: An all-MLP Architecture for Vision

Reference 25

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arxiv_id, observed 2026-06-26T18:59:43.602552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-26T18:55:03.636902Z digest=sha256:5aed11ef779ebb565e898b8b08cc6e72ce50c4b38c14051c65f7bd3281757fe1

Observation dee163ee-d986-46a2-b822-f3a172581466 · inbound

Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns cites this paper.

Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns MLP-Mixer: An all-MLP Architecture for Vision

Reference 20

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arxiv_id, observed 2026-07-04T17:29:59.843603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-25T23:43:20.900414Z digest=sha256:87f19cd2c9c646f96047ac0352b121d0cc7cf73aa69481852bff5222601ad86f

Observation 64b51f20-1ebf-4d50-8fde-ae58f86f0d72 · inbound

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks cites this paper.

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks MLP-Mixer: An all-MLP Architecture for Vision

Reference 49

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arxiv_id, observed 2026-07-01T15:45:48.384837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T01:10:12.636354Z digest=sha256:6324a35a4faaa1fdb7cc9283fb6e7577564ca6128a0b5d124556a6092cd4f345

Observation 65d79a19-00dc-4f3d-8067-70480e2b0d25 · inbound

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks cites this paper.

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks MLP-Mixer: An all-MLP Architecture for Vision

Reference 49

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arxiv_id, observed 2026-07-01T09:35:40.089589Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-01T06:27:54.229184Z digest=sha256:0f53d32f953c6ebf60ee7c5bbe86ff2f1e5b0eea9c1add28f8fd9e86433090c7

Observation efe04ea0-27e4-4299-b4e3-7036eae6b03b · inbound

Transformer-based machine learning using low-level calorimeter signals for collimated photon identification at collider experiments cites this paper.

Transformer-based machine learning using low-level calorimeter signals for collimated photon identification at collider experiments MLP-Mixer: An all-MLP Architecture for Vision

Reference 42

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local_arxiv, observed 2026-07-10T11:57:03.319850Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation dc51db23-523f-4cc2-ac72-2ef627b9917f · inbound

A Lightweight Foundation Model for Collider Physics with Multi-Domain Adaptation cites this paper.

A Lightweight Foundation Model for Collider Physics with Multi-Domain Adaptation MLP-Mixer: An all-MLP Architecture for Vision

Reference 18

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source=pdf_text observed=2026-08-01T06:46:58.439106Z digest=sha256:5640ffd068b2a0d6ad3b785a70847ba76614de5804b6e9c61c6b8e694e0538fb

Observation 564e44f8-64bf-498c-9061-3d99d7112d25 · inbound

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer cites this paper.

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer MLP-Mixer: An all-MLP Architecture for Vision

Reference 5

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no resolver link, observed 2026-08-03T16:12:10.026048Z

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source=pdf_text observed=2026-08-03T16:12:10.026048Z digest=sha256:624b5d145af207c5e9f0b08930e6e0fffe067c9998ddaae6da76071bcbd0cfd2

Observation 51df6c22-dd1b-43ca-bb17-dd707ba67634 · inbound

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces cites this paper.

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces MLP-Mixer: An all-MLP Architecture for Vision

Reference 19

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