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Paper Citation Record · LEDGER

Exploring Visual Prompting: Robustness Inheritance and Beyond

As of 8 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2506.06823.

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

pith.paper-citation-record.v1
2506.06823 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:52:38.803069Z

measured 50 of 50 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 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

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation be90a55f-864d-490f-9959-274a180dbc23 · outbound

This paper cites Feature purification: How adversarial training performs robust deep learning.

Exploring Visual Prompting: Robustness Inheritance and Beyond Feature purification: How adversarial training performs robust deep learning

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.222225Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.652101Z digest=sha256:729159c7abd345f791148b8e3d7f7869056e79e05cb1731efa203860b60b990f

Observation 0a91bcad-9e1b-4a6a-8e5e-861009a9bf32 · outbound

This paper cites Exploring Visual Prompts for Adapting Large-Scale Models.

Exploring Visual Prompting: Robustness Inheritance and Beyond Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.655882Z digest=sha256:e6170261ec1a4f1bf7a6b5fce2d825f18d31e440413ae5ceffefcb0b62e88abe

Observation db0546ec-d6a8-4f44-a33e-d7c485bfd0bd · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Exploring Visual Prompting: Robustness Inheritance and Beyond BEiT: BERT Pre-Training of Image Transformers

Reference 3

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no resolver link, observed 2026-08-07T05:52:38.659389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.659389Z digest=sha256:feeeee8d256a38441267d13a1e38df5445195191adeafea6d9a3aacf96142bd5

Observation dd74ce99-448e-447d-9669-7420016c4f57 · outbound

This paper cites Language models are few-shot learners.

Exploring Visual Prompting: Robustness Inheritance and Beyond Language models are few-shot learners

Reference 4

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no resolver link, observed 2026-08-07T05:52:38.662800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.662800Z digest=sha256:9195c88b4ef5852567e8094be82376c4448ec3cc6af02f60d1fba3e910fc2a71

Observation 6831fd56-50da-486c-be01-9f1636fa53cb · outbound

This paper cites Adversarial Attacks and Defences: A Survey.

Exploring Visual Prompting: Robustness Inheritance and Beyond Adversarial Attacks and Defences: A Survey

Reference 5

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unresolved
no resolver link, observed 2026-08-07T05:52:38.665955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.665955Z digest=sha256:6b7a1ba3fc53e7384fa3f7d421baae90d4b4cf78bc98660ab2afb039a1857f6a

Observation 40d50b67-e859-4399-b979-1357754bc7a7 · outbound

This paper cites Jacobian Adversarially Regularized Networks for Robustness.

Exploring Visual Prompting: Robustness Inheritance and Beyond Jacobian Adversarially Regularized Networks for Robustness

Reference 6

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unresolved
no resolver link, observed 2026-08-07T05:52:38.669361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.669361Z digest=sha256:6a8df39e8d525662c722f9a2c006503f8db0d148e9f33d4ee7ba75de7ef4cdce

Observation 8034c0fc-81a4-4634-9f95-e865901a49cf · outbound

This paper cites Exploring simple siamese representation learning.

Exploring Visual Prompting: Robustness Inheritance and Beyond Exploring simple siamese representation learning

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.208704Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.672904Z digest=sha256:9d034f760910d8f315d708ee6c8678b3a73f9e4026ed01046348a269376e7af7

Observation cadcc301-bcf4-4414-b673-3106ef071c53 · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recognition.

Exploring Visual Prompting: Robustness Inheritance and Beyond Adaptformer: Adapting vision transformers for scalable visual recognition

Reference 8

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raw_fallback, observed 2026-08-07T05:52:39.200317Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.675989Z digest=sha256:f2902c485b66d903fefa217815c239beeaf571c772740ea19ca6fd8f1f763451

Observation a5b3ae90-ef93-4d66-b9dc-5936ac4a83b1 · outbound

This paper cites Visual prompting for adversarial robustness.

Exploring Visual Prompting: Robustness Inheritance and Beyond Visual prompting for adversarial robustness

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.191750Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.679217Z digest=sha256:78c6260dba795495a329f4642d1776e2719586a42b61143e116d1e529e99b04d

Observation 2cfb01bc-b9db-47cc-8ec1-bafecb2e8270 · outbound

This paper cites Understanding and improving visual prompting: A label-mapping perspective.

Exploring Visual Prompting: Robustness Inheritance and Beyond Understanding and improving visual prompting: A label-mapping perspective

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.182671Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.681959Z digest=sha256:a91c60a3ca993124e0f0815ae66efc7a0d50784d05e10e4ead51df4cbba355e0

Observation 794c2c7f-1b34-4f6e-9166-2387587a7499 · outbound

This paper cites Describing textures in the wild.

Exploring Visual Prompting: Robustness Inheritance and Beyond Describing textures in the wild

Reference 11

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no resolver link, observed 2026-08-07T05:52:38.684502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.684502Z digest=sha256:91a9b385b24c92e5adbe0f5d8311326b792195f29917911ecb0f66c2887f70df

Observation f9033e02-70b0-4f1a-90d9-514792290ca9 · outbound

This paper cites Minimally distorted adversarial examples with a fast adaptive boundary attack.

Exploring Visual Prompting: Robustness Inheritance and Beyond Minimally distorted adversarial examples with a fast adaptive boundary attack

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.168925Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.687246Z digest=sha256:1f6388aa022bad089f4d0c840eded324c2ff22aa8020168bb55e064cff41930d

Observation 43d8b292-2c80-4827-9446-7d2a3fc339e5 · outbound

This paper cites Robustbench: a standardized adversarial robustness benchmark.

Exploring Visual Prompting: Robustness Inheritance and Beyond Robustbench: a standardized adversarial robustness benchmark

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.159992Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.689843Z digest=sha256:8d2741bf95740d9b0f7775c8d6d60f73929821fa7e9ba9e7f29ee74f0dfd6e68

Observation 13aca353-39c5-4bb3-8f34-2ad6877b926e · outbound

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

Exploring Visual Prompting: Robustness Inheritance and Beyond Imagenet: A large-scale hierarchical image database

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.692417Z digest=sha256:f5a94d12adda102218522913145a030ee219124c627a2a27d8fbad97483bfca4

Observation f66841c1-4c74-4ee5-bfce-8872f0e7f773 · outbound

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

Exploring Visual Prompting: Robustness Inheritance and Beyond BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 15

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unresolved
no resolver link, observed 2026-08-07T05:52:38.695152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.695152Z digest=sha256:e47e9029c34884da2ebdec2dab8486b8e69da41d86456b48de153cf85fd1754d

Observation 11210e21-3d78-4c0e-aaf8-3a2b923d360e · outbound

This paper cites Adversarial Reprogramming of Neural Networks.

Exploring Visual Prompting: Robustness Inheritance and Beyond Adversarial Reprogramming of Neural Networks

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.698813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.698813Z digest=sha256:4aa7f8751d7ecd95478ecf522d32beda631e1d3a93782e054080bebb56be9bbc

Observation 8a8b3a19-ae4c-4d53-9d91-d7f627cddd1e · outbound

This paper cites Robustness (python library), 2019.

Exploring Visual Prompting: Robustness Inheritance and Beyond Robustness (python library), 2019

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.146199Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.701799Z digest=sha256:bf0d364d4a910d7194677170c8b298703fce3fb09adad8d9ba47b657300b2f7d

Observation 4979c570-c3af-424d-842c-3ac5af6a341b · outbound

This paper cites Domain-adversarial training of neural networks.

Exploring Visual Prompting: Robustness Inheritance and Beyond Domain-adversarial training of neural networks

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.137543Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.704669Z digest=sha256:bc297f536dba8468caf3ca64e3699132c3fc926b3fdfba52edfada051bca3238

Observation 19138e8e-205b-4429-ba2a-902df54f823e · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Exploring Visual Prompting: Robustness Inheritance and Beyond Explaining and Harnessing Adversarial Examples

Reference 19

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no resolver link, observed 2026-08-07T05:52:38.707441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.707441Z digest=sha256:381a00e9cbafe0c88d029ee866e3d17a36cc5b3520b5b036daa706065d2263aa

Observation ed2d6bc6-b511-4020-8fe2-5fd066aff014 · outbound

This paper cites Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples.

Exploring Visual Prompting: Robustness Inheritance and Beyond Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples

Reference 20

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no resolver link, observed 2026-08-07T05:52:38.710291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.710291Z digest=sha256:10246e517a5f6e1aea5442169721f1c963d4617cd9309be9381851055df51199

Observation 26f8893d-0c12-48db-8c99-8eb056a57d14 · outbound

This paper cites Introducing eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

Exploring Visual Prompting: Robustness Inheritance and Beyond Introducing eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.128387Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.713183Z digest=sha256:24d97829b1cefe629d7b185dfb8967c6c7b5128c3b314feb77ccc8f37117aac3

Observation dfc1e3e6-d25f-49ae-a523-4b117d11c94a · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

Exploring Visual Prompting: Robustness Inheritance and Beyond Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.119388Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.715931Z digest=sha256:ff98ba90801d9d6ffc08eb0b318e5b9ed33eb0af833b887ab9fb62e811aad432

Observation ea86efcd-a130-49ab-b0c8-ad247ea2dcb2 · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

Exploring Visual Prompting: Robustness Inheritance and Beyond Universal Language Model Fine-tuning for Text Classification

Reference 23

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no resolver link, observed 2026-08-07T05:52:38.718746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.718746Z digest=sha256:852678356c12b73acb143296cb29597dce9bb4ca69cb4928c2e4079c0959d96e

Observation d374bff3-bb92-4487-9f5f-809ddfdc1fda · outbound

This paper cites Black-box adversarial attacks with limited queries and information.

Exploring Visual Prompting: Robustness Inheritance and Beyond Black-box adversarial attacks with limited queries and information

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.110496Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.721747Z digest=sha256:176fed236e7b114617781651c7f73641c0eb89f6813c2537c6b50855e766d762

Observation 84fc7a6f-a6fb-413d-ba85-35d62e7e5ab9 · outbound

This paper cites Visual prompt tuning.

Exploring Visual Prompting: Robustness Inheritance and Beyond Visual prompt tuning

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.101875Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.724471Z digest=sha256:700da623f42f6d3d4d031b41515531d34f73742db90951b9300a995be1bd5068

Observation 275a57ca-23f7-47f0-adc0-2b7f0563b313 · outbound

This paper cites 3d object representations for fine-grained categorization.

Exploring Visual Prompting: Robustness Inheritance and Beyond 3d object representations for fine-grained categorization

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.093273Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.727408Z digest=sha256:595f3af3d17e17657d88bb948174da0cf570f93a39d3b850bb2251b8468ec82f

Observation 96880a59-42a6-4505-bc3a-8c30d29e1d71 · outbound

This paper cites Learning multiple layers of features from tiny images.

Exploring Visual Prompting: Robustness Inheritance and Beyond Learning multiple layers of features from tiny images

Reference 27

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unresolved
no resolver link, observed 2026-08-07T05:52:38.730533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.730533Z digest=sha256:a6cf1ce5c6d9276de8b519b5074338e56dc890b3bae6d94db848848037cf4ea2

Observation 30b08d03-e3ac-4920-9bb1-178b7d2dc87c · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

Exploring Visual Prompting: Robustness Inheritance and Beyond Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 28

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unresolved
no resolver link, observed 2026-08-07T05:52:38.733405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.733405Z digest=sha256:c2effc1cefa75c2ab9c083eab77970ca17dfc6108b84f68414102a406768d548

Observation c7400179-71aa-4f55-a53c-b7a004470a69 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Exploring Visual Prompting: Robustness Inheritance and Beyond Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.736530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.736530Z digest=sha256:54494f742e7a184f96c3621280fa27a43b3c11332ab36bcf0fcc38063e47441f

Observation ebaea4e3-5ff5-4ef0-bd24-31d58abf821f · outbound

This paper cites Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.

Exploring Visual Prompting: Robustness Inheritance and Beyond Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing

Reference 30

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unresolved
no resolver link, observed 2026-08-07T05:52:38.740366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.740366Z digest=sha256:e88ee00540b37cc5e883c642bce2953fa61c6ad0eb8d7db07cf4e88a9befb5c0

Observation ae73ca36-baa0-4ca8-a48e-184fffb45fbe · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Exploring Visual Prompting: Robustness Inheritance and Beyond Towards deep learning models resistant to adversarial attacks

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.074014Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.743265Z digest=sha256:986871c00984042fbca67eb72f2d472f82a026e4a16e163cba8ccdbaa158b6f5

Observation 91be8d17-53ce-4ab9-88bb-82b0a6df9167 · outbound

This paper cites Reading digits in natural images with unsupervised feature learning.

Exploring Visual Prompting: Robustness Inheritance and Beyond Reading digits in natural images with unsupervised feature learning

Reference 32

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unresolved
no resolver link, observed 2026-08-07T05:52:38.745961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.745961Z digest=sha256:99afdf2363cf58fd5c774021eea2ad26d76db136ecbbf1a1a210962cb5018043

Observation c5619f0b-62c2-43bf-9433-948eede0e223 · outbound

This paper cites Automated flower classification over a large number of classes.

Exploring Visual Prompting: Robustness Inheritance and Beyond Automated flower classification over a large number of classes

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.060353Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.748812Z digest=sha256:9addb60ef8ad842705588eac207b31076718ed5ffa3078aa5b5cf15991c270cb

Observation 55817c79-a374-4664-a015-1fa79010ed1f · outbound

This paper cites Blackvip: Black-box visual prompting for robust transfer learning.

Exploring Visual Prompting: Robustness Inheritance and Beyond Blackvip: Black-box visual prompting for robust transfer learning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.051347Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.754364Z digest=sha256:2dfc62f95bc1216957e321e53ffa8e2f08e6827172467a9c5cff1582c05156b9

Observation 7a740313-ed3f-41f2-807a-1727689b5f23 · outbound

This paper cites A survey on transfer learning.

Exploring Visual Prompting: Robustness Inheritance and Beyond A survey on transfer learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.042662Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.757270Z digest=sha256:b4cb31b1ce38b712451e27425a1badf14dbcc5313b99918f4638e21852283e44

Observation a45d7c11-c905-4018-a03d-c5730a4c3a61 · outbound

This paper cites Robustness and accuracy could be reconcilable by (proper) definition.

Exploring Visual Prompting: Robustness Inheritance and Beyond Robustness and accuracy could be reconcilable by (proper) definition

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.034152Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.760107Z digest=sha256:5113724a8787ef123c6ae70ea2fcc5c2b6f9e022dc70e1fe7cedd81afb0458e6

Observation 55a94cf8-14c6-4519-9826-20afc06d8fc3 · outbound

This paper cites Cats and dogs.

Exploring Visual Prompting: Robustness Inheritance and Beyond Cats and dogs

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.025481Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.762890Z digest=sha256:8f3d926f5b88ea09a9278b2ed0034d2bcd8d4f54c08cb7db0b46d746007d9659

Observation 6966e259-b131-4a56-b25b-c2785c9908d3 · outbound

This paper cites Do adversarially robust imagenet models transfer better? Advances in Neural Information Processing Systems , 33:3533--3545, 2020.

Exploring Visual Prompting: Robustness Inheritance and Beyond Do adversarially robust imagenet models transfer better? Advances in Neural Information Processing Systems , 33:3533--3545, 2020

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.016566Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.765644Z digest=sha256:b2f9c46ffcbd2d2119a0d6b46c83bd96038a767c95c2dcef3892f00194510029

Observation e6037660-a8ce-469a-8e8c-e754bc10d79d · outbound

This paper cites Adversarial training for free! Advances in Neural Information Processing Systems , 32, 2019.

Exploring Visual Prompting: Robustness Inheritance and Beyond Adversarial training for free! Advances in Neural Information Processing Systems , 32, 2019

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:39.006742Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.768543Z digest=sha256:a9c7b36c1972d29b1359459e8b64359e259cefdabb17fbae36b9aafc1ed72b38

Observation b0ed7865-3773-451e-8196-a371bc4206ef · outbound

This paper cites The german traffic sign recognition benchmark: a multi-class classification competition.

Exploring Visual Prompting: Robustness Inheritance and Beyond The german traffic sign recognition benchmark: a multi-class classification competition

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:38.997453Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.771378Z digest=sha256:45b4dde8c5723beb503b3b7fe819be061ad9aaa2d2e76eeff7061e485e4aa15b

Observation 94442439-be8b-463f-b78b-96843576c8f2 · outbound

This paper cites Adversarial training and robustness for multiple perturbations.

Exploring Visual Prompting: Robustness Inheritance and Beyond Adversarial training and robustness for multiple perturbations

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:38.987796Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.774264Z digest=sha256:da62a2638bef3fc414bc159e86e175e99a169a9f56f3feafd06cfc42051f54d6

Observation fb0976df-d0a7-4395-96e8-6f1eb14a985f · outbound

This paper cites Ensemble Adversarial Training: Attacks and Defenses.

Exploring Visual Prompting: Robustness Inheritance and Beyond Ensemble Adversarial Training: Attacks and Defenses

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.777178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.777178Z digest=sha256:0bed66221d0527fd9394acbd735c77e728132a49cd624293d453a1d583d8c1ce

Observation 1920bb60-5d9b-48e0-944d-fff9807bc34f · outbound

This paper cites Transfer learning without knowing: Reprogramming black-box machine learning models with scarce data and limited resources.

Exploring Visual Prompting: Robustness Inheritance and Beyond Transfer learning without knowing: Reprogramming black-box machine learning models with scarce data and limited resources

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:38.977835Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.780453Z digest=sha256:012feeca4a9701945cf6b2449d29ca638fb0e0e3ca346a41e81aadecd7045c73

Observation b9d6e3c9-c7d1-48fb-90a7-2e6496462015 · outbound

This paper cites Robustness May Be at Odds with Accuracy.

Exploring Visual Prompting: Robustness Inheritance and Beyond Robustness May Be at Odds with Accuracy

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.783200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.783200Z digest=sha256:c49cf788fa9f45e532b3d96e3d7e441f79676c460555ce0809f9212ed253bffa

Observation 1f5b517e-d3a8-4453-91df-f2ce7a181814 · outbound

This paper cites Bilateral adversarial training: Towards fast training of more robust models against adversarial attacks.

Exploring Visual Prompting: Robustness Inheritance and Beyond Bilateral adversarial training: Towards fast training of more robust models against adversarial attacks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:38.968843Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.786354Z digest=sha256:7f848b816d847982c5ec1148f8f046e942551942094f04cf19747a3d0a4deb41

Observation 7e6851c5-afb0-4cac-8e71-5f8cd182370e · outbound

This paper cites Pytorch image models.

Exploring Visual Prompting: Robustness Inheritance and Beyond Pytorch image models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.789218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.789218Z digest=sha256:1102fe18762b7f3d91e1ddc692b6fd2670cd48884755973b49d8d34627158ae2

Observation fa0017ca-1635-40da-a89b-cc931e096942 · outbound

This paper cites Fast is better than free: Revisiting adversarial training.

Exploring Visual Prompting: Robustness Inheritance and Beyond Fast is better than free: Revisiting adversarial training

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.793561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.793561Z digest=sha256:6a713feadf741b39570a4a353b1fb4b41128953f716ef0761898557eecd52177

Observation 57c3b6d3-32aa-4585-bbd9-7561319075e4 · outbound

This paper cites Conditional prompt learning for vision-language models.

Exploring Visual Prompting: Robustness Inheritance and Beyond Conditional prompt learning for vision-language models

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:38.954964Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.797572Z digest=sha256:4c018ce3a8b0f56597b049f64834f308e511104b63d5f502a81576a42e717abf

Observation 81db3a34-b2a6-4c2e-9d67-5434157ea235 · outbound

This paper cites Learning to prompt for vision-language models.

Exploring Visual Prompting: Robustness Inheritance and Beyond Learning to prompt for vision-language models

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:52:38.945882Z

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.

source=arxiv_source observed=2026-08-07T05:52:38.800307Z digest=sha256:0734d3ec50a282e30653204d0d70f863dbef11b766300e607233fa48bf11917d

Observation 47a32795-ce8b-415d-9a96-09e9d7a4e553 · outbound

This paper cites write newline.

Exploring Visual Prompting: Robustness Inheritance and Beyond write newline

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:38.803069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:52:38.803069Z digest=sha256:70ffe3bda31b1ae9acab802a7695dc8003d70e13c8b94d9308a9ae5c2f2c6c1b

Pith citing papers

No inbound Pith citation observations are available.