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Paper Citation Record · LEDGER

One Pixel is All I Need

As of 12 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2412.10681.

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

pith.paper-citation-record.v1
2412.10681 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:48:26.968010Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

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

51 of 51 outbound references displayed

  • verified exact1
  • verified fuzzy22
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d0321a6-ce42-4071-adae-e300e4b1d60c · outbound

This paper cites Reveal of Vision Transformers Robustness against Adversarial Attacks.

One Pixel is All I Need Reveal of Vision Transformers Robustness against Adversarial Attacks

Reference 1

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source=pdf_text observed=2026-08-11T15:48:25.514442Z digest=sha256:fbd4d2a52be03ab495430871d8a682358de3b4037fdb0f363d2d9089e37706a3

Observation 81154c4d-8952-4b78-b839-f71343c8d150 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

One Pixel is All I Need Neural Machine Translation by Jointly Learning to Align and Translate

Reference 2

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source=pdf_text observed=2026-08-11T15:48:25.526615Z digest=sha256:01adcf70b63df9e67116eb2aadceed58b3f19ce08d6eac3a35619888ce509236

Observation 67394a5c-3480-452c-bbc3-2563b0ef857f · outbound

This paper cites Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits.

One Pixel is All I Need Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits

Reference 3

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source=pdf_text observed=2026-08-11T15:48:25.588768Z digest=sha256:545323aae4ed377e2ad769084edb58207fb44ca6e6be43a66e79fcbd11630e6b

Observation 9f45b025-262c-449e-b21d-7833cf09984c · outbound

This paper cites Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs.

One Pixel is All I Need Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs

Reference 4

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source=pdf_text observed=2026-08-11T15:48:25.761719Z digest=sha256:f7ec3b6efa7df5b0ccc3fa16d7984bc6df0b3e264cfcbf758b7ef56a9a4f72d1

Observation eb05d464-b579-4153-aea0-012caa22ed4f · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

One Pixel is All I Need Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 5

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source=pdf_text observed=2026-08-11T15:48:25.766910Z digest=sha256:df27f89a965ec52ea76248fc9685a288fb205a7ae4b2cd92037b0d009a98c5e2

Observation 4e32a0a3-5f4d-4b0e-8c03-afd4bc16954e · outbound

This paper cites Visformer: The vision-friendly transformer.

One Pixel is All I Need Visformer: The vision-friendly transformer

Reference 6

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:25.771958Z digest=sha256:caa9fd2264073ad959ec2b34c3fdad48d8b6ee8de320da8fe1183b8bffcb3265

Observation 010b5964-37bb-4bfb-9fbf-54eb2e34d638 · outbound

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

One Pixel is All I Need BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 7

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source=pdf_text observed=2026-08-11T15:48:25.776695Z digest=sha256:7c42c9cfa86ec1b3dfb65a2a7ccf373f8039cc3ff7f36b982c0a5c14872db675

Observation 75d1a22e-86ac-4b17-9afe-882d3c9a30b8 · outbound

This paper cites Lira: Learnable, imperceptible and robust backdoor attacks.

One Pixel is All I Need Lira: Learnable, imperceptible and robust backdoor attacks

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:25.781926Z digest=sha256:1a1f956aae98ce411d7a7b4403816192018f7bf4fa651577c40d807730a0e848

Observation 8d6d3815-6d9c-4e40-a588-3b2bfe6235b3 · outbound

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

One Pixel is All I Need An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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source=pdf_text observed=2026-08-11T15:48:25.786779Z digest=sha256:900c80fc7855ec91ccfea3177d859ce4d05a93b59730229357998a4bd7156a97

Observation 216f1dfd-d13e-465d-8441-445f2b48e399 · outbound

This paper cites Fiba: Frequency-injection based backdoor attack in medical image analysis.

One Pixel is All I Need Fiba: Frequency-injection based backdoor attack in medical image analysis

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:25.790830Z digest=sha256:bb0613b83c87e3143f817f9000ee46a3ff26f5690e47734ffc9258b9fdeea33a

Observation 385097dd-a3c0-4e40-9915-db628c10c7d4 · outbound

This paper cites Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoning.

One Pixel is All I Need Backdoor Attack on Hash-based Image Retrieval via Clean-label Data Poisoning

Reference 11

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:25.795039Z digest=sha256:374a84ee880ee6fcc5498c9bfec74f1a0b038fad401af78c2871cb74e38a4c5a

Observation 87bba81c-ceac-4849-9180-ea042a3f4cc7 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

One Pixel is All I Need Explaining and Harnessing Adversarial Examples

Reference 12

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source=pdf_text observed=2026-08-11T15:48:25.986513Z digest=sha256:8a9dc945017cd34d5f8fa14933c7eec3f8a89f96fd42c22acf5e5620f7251f27

Observation 117e5c92-7527-4511-885f-157d419bac20 · outbound

This paper cites BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.

One Pixel is All I Need BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 13

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source=pdf_text observed=2026-08-11T15:48:25.991577Z digest=sha256:759e45216f41cddf4b2b10e316c6c326c0ba4245f106678fe5179b611b0739b8

Observation f7c7dd04-5fae-4307-9468-a1b53b7138db · outbound

This paper cites SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency.

One Pixel is All I Need SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency

Reference 14

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source=pdf_text observed=2026-08-11T15:48:25.995940Z digest=sha256:bbd33fa5714ce1a65a75c41f40b611bd3759e3e05300d251b0ccf921247499b0

Observation 029dbb49-9027-478e-a27e-546ed2805dec · outbound

This paper cites Transformer in transformer.

One Pixel is All I Need Transformer in transformer

Reference 15

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source=pdf_text observed=2026-08-11T15:48:26.000398Z digest=sha256:68a5511a3a5c4eeee4eeee67a597b77029bdffa0dbe7574254fbc16bf52aea41

Observation 20f5a202-11d2-44c8-8a1d-da460a9fcda3 · outbound

This paper cites Rethinking spa- tial dimensions of vision transformers.

One Pixel is All I Need Rethinking spa- tial dimensions of vision transformers

Reference 16

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source=pdf_text observed=2026-08-11T15:48:26.004648Z digest=sha256:9910ec511dc849d80a9be624372ecec323dd1938cd1b5c4cbae6ac844e25bd67

Observation cf4a68b8-3272-49c8-b1af-e4303e15d707 · outbound

This paper cites ALBERT: A Lite BERT for Self-supervised Learning of Language Representations.

One Pixel is All I Need ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Reference 17

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source=pdf_text observed=2026-08-11T15:48:26.134500Z digest=sha256:bc768c3839fbce5fa8403d94848293681b8fcc6bd8c5e1db3612fa7987cb1e0f

Observation d32ef89e-0995-41bb-8610-07c142e16548 · outbound

This paper cites Nearest is not dearest: Towards practical defense against quantization-conditioned backdoor attacks.

One Pixel is All I Need Nearest is not dearest: Towards practical defense against quantization-conditioned backdoor attacks

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.139189Z digest=sha256:43a25c4ebd4409963782a1caea87fc17ad37e54f01cd46202a8fb6dca547e5bc

Observation e13415ac-17d6-4bd7-94ae-0ca95fe72741 · outbound

This paper cites Rethinking the Trigger of Backdoor Attack.

One Pixel is All I Need Rethinking the Trigger of Backdoor Attack

Reference 19

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source=pdf_text observed=2026-08-11T15:48:26.143347Z digest=sha256:adb62de4b7e477ecab4f2bd892d16dcf674fa732dad8cafa9f9daf6918cdd327

Observation c0fcaab3-806d-4aa0-933a-a511cea6e276 · outbound

This paper cites Back- door learning: A survey.

One Pixel is All I Need Back- door learning: A survey

Reference 20

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source=pdf_text observed=2026-08-11T15:48:26.147559Z digest=sha256:40b450c7bd74d93115c3c189c4988ce3ebf84cb34f0a222e1a31b7cd31aa2c0d

Observation 9f8cfa54-4186-476b-89aa-e9d0be6f8f25 · outbound

This paper cites Efficientformer: Vision transformers at mobilenet speed.

One Pixel is All I Need Efficientformer: Vision transformers at mobilenet speed

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.151579Z digest=sha256:a6f79a5832b99076a98bf3e97489e0cf94f79a26f94af6b47aed5117e61e2f21

Observation a2bbef42-8c62-4297-afb2-0d2224aece26 · outbound

This paper cites Imperceptible transfer attack and defense on 3d point cloud classification.

One Pixel is All I Need Imperceptible transfer attack and defense on 3d point cloud classification

Reference 22

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.155293Z digest=sha256:15e407f2f8a806d2fb3e911f39ff1a8a9cadac3bc3578e84c13a7f013fdcf89b

Observation 6b35a6e3-2a61-43db-89f2-3ac0a35e9d6d · outbound

This paper cites Fine- pruning: Defending against backdooring attacks on deep neural networks.

One Pixel is All I Need Fine- pruning: Defending against backdooring attacks on deep neural networks

Reference 23

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source=pdf_text observed=2026-08-11T15:48:26.159180Z digest=sha256:193d5cd26d047610741db0ed9de11e99e7af7a238b6a169d38503858a9546ae8

Observation 4ec66ea0-02d2-448a-aaea-47bddab6e850 · outbound

This paper cites Beating backdoor attack at its own game.

One Pixel is All I Need Beating backdoor attack at its own game

Reference 24

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.164125Z digest=sha256:810e10aa2cc1c6f8f51029987469cb0d592b56a2d704f9aafd50c240591b0ef3

Observation b93b08ac-5680-4c37-a13e-8ad9f374cc59 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

One Pixel is All I Need RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 25

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source=pdf_text observed=2026-08-11T15:48:26.167858Z digest=sha256:2ae13e4a1cae70626387250558909147ac4fc80a7a97ff8c43b23e5d699c4447

Observation e11e857a-7f90-4696-a1a7-be2c8694e8b3 · outbound

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

One Pixel is All I Need Swin transformer: Hierarchical vision transformer using shifted windows

Reference 26

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.287335Z digest=sha256:0299e92c9e36d487521b5655f49d0d2c6d4479df99c837698246e89bb3444f20

Observation b40864a8-7efa-42fd-9510-9c9f897ca972 · outbound

This paper cites TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition.

One Pixel is All I Need TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition

Reference 27

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source=pdf_text observed=2026-08-11T15:48:26.402855Z digest=sha256:155de67cdca6c8438f3c4f9050c72ba2c822c71eef91e3c4b8992cc04abf285d

Observation ea22deab-1edb-476f-8198-24275d8b90d4 · outbound

This paper cites On the robustness of vision transformers to adversarial ex- amples.

One Pixel is All I Need On the robustness of vision transformers to adversarial ex- amples

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.525737Z digest=sha256:1d43a6679b0ea8a5f460bdba06f255a612157a4ae43e4c332863f0e4ac41532a

Observation 10993688-3a16-4a47-81a3-d120445b21fa · outbound

This paper cites Hidden trigger backdoor attacks.

One Pixel is All I Need Hidden trigger backdoor attacks

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.530501Z digest=sha256:3d2e4a8070f604073227d9c910b86851f5a2596dcb19e910155370cf0a31ef57

Observation f01f191a-f10d-4d4a-ae00-c259c5b2cad6 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

One Pixel is All I Need Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 30

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source=pdf_text observed=2026-08-11T15:48:26.535004Z digest=sha256:8b079a04bcde0e205cb2432e06635d29e488703145614e11484c962c44494cc2

Observation d933ff43-8a77-46a3-a02b-7a2d517af8bd · outbound

This paper cites SmoothGrad: removing noise by adding noise.

One Pixel is All I Need SmoothGrad: removing noise by adding noise

Reference 31

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source=pdf_text observed=2026-08-11T15:48:26.539442Z digest=sha256:332e63d11ed0a5fa8f2fc0d3c8ad33c49b41ba6c3c7a136d58b4aa3dec54b0c1

Observation 136f4d20-bb0a-4638-b71a-cb40dbb067b8 · outbound

This paper cites Segmenter: Transformer for semantic segmenta- tion.

One Pixel is All I Need Segmenter: Transformer for semantic segmenta- tion

Reference 32

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source=pdf_text observed=2026-08-11T15:48:26.544054Z digest=sha256:9b75552acd9c596bc2c941c3a73b1a37af62fc71be7e5532b8f6909dc2af73fd

Observation 9423e430-5684-46ce-b37f-aa26a5092db7 · outbound

This paper cites One pixel attack for fooling deep neural networks.

One Pixel is All I Need One pixel attack for fooling deep neural networks

Reference 33

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source=pdf_text observed=2026-08-11T15:48:26.549083Z digest=sha256:c47a1273a78638d941b7c3d3f1ae33b5795aeb8cbce69fc5d7f3daa41f418041

Observation ed8474ce-23c8-4260-ab67-8c08bf1ed0d1 · outbound

This paper cites Backdoor attacks on crowd counting.

One Pixel is All I Need Backdoor attacks on crowd counting

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.553913Z digest=sha256:54877c952e6cdf32e012a20b97077196e3827e2ae43b5aa65145a078eefcccb9

Observation aedebd3e-06b2-4bf6-88fd-4d8d0721f982 · outbound

This paper cites Intriguing properties of neural networks.

One Pixel is All I Need Intriguing properties of neural networks

Reference 35

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source=pdf_text observed=2026-08-11T15:48:26.558129Z digest=sha256:6600a596f024e3ddf5a7bcf46947bd18193263d1854af272670626eea0b76f06

Observation 60b8b67f-fe54-4202-b201-4cfb5c2901ee · outbound

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

One Pixel is All I Need Training data-efficient image transformers & distillation through at- tention

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.562002Z digest=sha256:b78c320c55854a807df03b9e4147a144ecd707dbe871b8933c0ebc4d53a4e083

Observation 889b58f2-ca50-4fb5-a7e7-0015a754359e · outbound

This paper cites Attention is all you need.

One Pixel is All I Need Attention is all you need

Reference 37

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source=pdf_text observed=2026-08-11T15:48:26.567289Z digest=sha256:d1de75c66c5f394766ac48ea6b706399b2b69a7f063e42c81a90e7049f4b4acb

Observation 63a7eca9-704b-4de0-8ffc-7d7ab422cbbd · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neu- ral networks.

One Pixel is All I Need Neural cleanse: Identifying and mitigating backdoor attacks in neu- ral networks

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-11T15:48:28.079041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.571690Z digest=sha256:4f0486253fa478ba78ea8d38002f5f4ccfc8c844c9299169e924eee7191eeb11

Observation bdca4043-4a28-4f34-9b49-11d6fa67446e · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions.

One Pixel is All I Need Pyramid vision transformer: A versatile backbone for dense prediction without convolutions

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:26.731645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:26.731645Z digest=sha256:7d3bf040b92de9fecbc92aea8e7bcb68409da8fe3906d11409f69f0727411c6f

Observation 104b0338-e840-4e69-89d4-4496c0edbe9f · outbound

This paper cites Early convolutions help trans- formers see better.

One Pixel is All I Need Early convolutions help trans- formers see better

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:26.835693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:26.835693Z digest=sha256:43c0acec08d42a169de1d62f0e8631f8127acba3dae3e8c149366172ee86f42b

Observation 97be5a95-d13f-460d-a134-b4025cc2432a · outbound

This paper cites Not all prompts are secure: A switch- able backdoor attack against pre-trained vision transfomers.

One Pixel is All I Need Not all prompts are secure: A switch- able backdoor attack against pre-trained vision transfomers

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:28.000886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.885039Z digest=sha256:73d76d30eab4cdfade7a237d098e7b893e5cd53386fe4710804546e57a546df8

Observation e497e697-02e6-435e-8b6d-50aa9b26c1b2 · outbound

This paper cites Gpt (generative pre-trained transformer)–a comprehensive review on enabling technolo- gies, potential applications, emerging challenges, and future directions.

One Pixel is All I Need Gpt (generative pre-trained transformer)–a comprehensive review on enabling technolo- gies, potential applications, emerging challenges, and future directions

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.933351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.931175Z digest=sha256:55d3a0e2b6676bc12514d03cde7f2af078f0b5245d599ff97c4082ef9238e419

Observation 2c172ec5-d0d7-4f74-bc2d-688a7173c08d · outbound

This paper cites Enhanced coalescence backdoor attack against dnn based on pixel gradient.

One Pixel is All I Need Enhanced coalescence backdoor attack against dnn based on pixel gradient

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.796574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.934844Z digest=sha256:9239754e5ad7d01e740f1b8af642630e046c9d3219a37e3bf550b7f1c8c00ad0

Observation 1c818f61-9ea1-4494-929f-93de72e542a6 · outbound

This paper cites Backdoor attacks against deep image compression via adaptive frequency trigger.

One Pixel is All I Need Backdoor attacks against deep image compression via adaptive frequency trigger

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.734330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.938857Z digest=sha256:e81e4bfb3cea5650c2914573952f7f89887ef3e9513854561033d7d4036e90c9

Observation 39bc17f6-d737-4dd5-8bae-a616f8b7f146 · outbound

This paper cites Tokens-to-token vit: Training vision transformers from scratch on imagenet.

One Pixel is All I Need Tokens-to-token vit: Training vision transformers from scratch on imagenet

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:26.942986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:26.942986Z digest=sha256:aeabb15126b01202be8e4796e55c428fd9f20c3b2dfb6127a72d1e38c18926b1

Observation feccaf97-ae1c-40ac-ab46-354b83724f39 · outbound

This paper cites an unresolved cited work.

One Pixel is All I Need Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-11T15:48:27.564513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.947339Z digest=sha256:d49a39df7f4e0e37fdff99bb200f05247b34b450f880fbefc6176a09f875631f

Observation c3e95a60-f604-49f9-af8a-800265888c56 · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecast- ing.

One Pixel is All I Need Informer: Beyond efficient transformer for long sequence time-series forecast- ing

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.549822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.951197Z digest=sha256:ff23d1d7e252787f8092cfabbb6f7f3f6a05ac805f7e68a110722957ec3ba599

Observation 9162ea49-5086-4d65-95f9-a5609ea186fc · outbound

This paper cites • Impact of PSDM on Backdoor Patterns: Based on the PSDM of the VIT model, we traversed multiple patches along the diagonal and placed a white square trigger of size 4 for training.

One Pixel is All I Need • Impact of PSDM on Backdoor Patterns: Based on the PSDM of the VIT model, we traversed multiple patches along the diagonal and placed a white square trigger of size 4 for training

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.536305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.955290Z digest=sha256:82d9c5d514d5b625ae426228a35ad8984cd37241ac6c8106f83983a8d4dd2a62

Observation 642296b0-23cd-4dfb-a068-8715c90c99c1 · outbound

This paper cites Lclean = E(x,y)∼Dclean [ℓ(f (x), y)] (1).

One Pixel is All I Need Lclean = E(x,y)∼Dclean [ℓ(f (x), y)] (1)

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.358564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.959581Z digest=sha256:6e8b827e5d76599ece8d530495e796afa5c42ca7e27203dd98e890465329f4f9

Observation 9b0bd0e8-ec04-4b57-9f45-3051982725f7 · outbound

This paper cites Lbackdoor = E(x,y)∼Dbackdoor [ℓ(f (x + t), ybackdoor)] (2).

One Pixel is All I Need Lbackdoor = E(x,y)∼Dbackdoor [ℓ(f (x + t), ybackdoor)] (2)

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.288378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.963723Z digest=sha256:20c5b90ecbd5f08ff78d2ec6a637d044a356509b0d0829db31c4245e2691bfd2

Observation df6ea9ad-9bca-4cd8-9746-e0ba154eb8e4 · outbound

This paper cites Lsuppression = E(x,y)∼Dpartial [ℓ(f (x + tpartial), yclean)] (3) The model does not always learn the backdoor suppres- sion mode effectively.

One Pixel is All I Need Lsuppression = E(x,y)∼Dpartial [ℓ(f (x + tpartial), yclean)] (3) The model does not always learn the backdoor suppres- sion mode effectively

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:27.273902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:48:26.968010Z digest=sha256:10721edda03850a8b74f5e1e805038e148795596aa7826c47e288219513461c6

Pith citing papers

No inbound Pith citation observations are available.