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Paper Citation Record · LEDGER

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation

As of 21 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2501.02704.

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

pith.paper-citation-record.v1
2501.02704 v3

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:10:36.611106Z

measured 41 of 41 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:10:36.611106Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T22:10:36.661421Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact0
  • verified fuzzy33
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36005ded-ced9-4dc3-9ab7-f793d30ad739 · outbound

This paper cites Attention is All you Need,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Attention is All you Need,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-10T22:10:37.506124Z

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=2026-08-10T22:10:36.362661Z digest=sha256:0ef6d38885a5a71217ba31b99e776215f82215bab689356dc94dd8740fd45bd0

Observation 03f9c932-07d5-4fe0-a85b-5a4a80c7f43e · outbound

This paper cites Language Models are Few-Shot Learners,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Language Models are Few-Shot Learners,

Reference 2

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no resolver link, observed 2026-08-10T22:10:36.369500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:36.369500Z digest=sha256:abb31af6eb7fd7750ac58a302d1b3e4cb739715bd49d76580033eaa80cb916b9

Observation e507fcf3-373b-4824-b0e1-e4b34bcf8cc9 · outbound

This paper cites GPT-4 Technical Report,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation GPT-4 Technical Report,

Reference 3

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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=2026-08-10T22:10:36.375414Z digest=sha256:3eebc3a4afa5362da157b8306e543bb710a7a2758a51ae1ca42504f257652d10

Observation 9d9b6908-4f5b-48bf-8033-0f3461d5fbf2 · outbound

This paper cites LaMDA: Language Models for Dialog Applica- tions,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation LaMDA: Language Models for Dialog Applica- tions,

Reference 4

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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=2026-08-10T22:10:36.382090Z digest=sha256:bcf5e06e664262e09828ad40a5b48c00ef2043a9da1ede0af5adbf2f339caff3

Observation e21858d6-54d0-4de1-89a4-02240150e1ec · outbound

This paper cites PaLM 2 Technical Report,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation PaLM 2 Technical Report,

Reference 5

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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=2026-08-10T22:10:36.388500Z digest=sha256:02aaf6845b3ecc84d8ab0fbb73775626c78a2a6634460a249bbf1fa253cbbd9c

Observation c2616cb0-c2a3-4267-b92e-b33c026e5299 · outbound

This paper cites MLaaS: Machine Learning as a Service,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation MLaaS: Machine Learning as a Service,

Reference 6

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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=2026-08-10T22:10:36.394390Z digest=sha256:0bf57ffe18817955528cd8f0c0a093723f427ad7568c74d468a107b78e70ea2e

Observation 274d7a88-106d-4374-8fdb-d44d5db65bd9 · outbound

This paper cites Embedding Water- marks into Deep Neural Networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Embedding Water- marks into Deep Neural Networks,

Reference 7

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raw_fallback, observed 2026-08-10T22:10:37.382355Z

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=2026-08-10T22:10:36.400315Z digest=sha256:62a09c02830d79a799b0a8eb484a95d7db47734c2ba73b497589dac6eaa96fa8

Observation 1ca1c7af-c62e-43c1-b19f-8f6c16af9715 · outbound

This paper cites Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring,

Reference 8

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:10:36.408093Z digest=sha256:112731e5d8cf43010d4c53d4b652f753f4eb679b91f1525d592d6d816bd0607d

Observation 26383cec-7260-4216-afab-63156f3ef695 · outbound

This paper cites On the Robustness of Backdoor-based Watermarking in Deep Neural Net- works,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation On the Robustness of Backdoor-based Watermarking in Deep Neural Net- works,

Reference 9

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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=2026-08-10T22:10:36.413753Z digest=sha256:b8440ff07da9c49e5cb77a7e0ae7fa822b789f3e280dbe3cf2a9d46c7b05a243

Observation 29204acd-abc5-4ee2-8136-c44a9ac577ed · outbound

This paper cites REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data,

Reference 10

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:10:36.419387Z digest=sha256:cd83597260633aec6d27a9b58437583d04e2a81650531762b7cf7787d13d315d

Observation 7b29bf4c-7a02-43ed-af0e-f7c9dcca9649 · outbound

This paper cites Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks,

Reference 11

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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=2026-08-10T22:10:36.424624Z digest=sha256:c9d99c13d36f30fa8676ba36bf31d9fc337ce4e5e46f40dda1bd2b30600d0497

Observation e0b51e55-2e9b-4e34-8076-06e0e39a8157 · outbound

This paper cites A survey of Deep Neural Network watermarking techniques,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation A survey of Deep Neural Network watermarking techniques,

Reference 12

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raw_fallback, observed 2026-08-10T22:10:37.283537Z

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=2026-08-10T22:10:36.429918Z digest=sha256:229a95300532ef031f1e489163243881a26a89ebd09c245a84fbd5c0be9135d3

Observation 903b8dc8-0092-43f8-b163-e5bdb69121ab · outbound

This paper cites DeepSigns: An End- to-End Watermarking Framework for Ownership Protection of Deep Neural Networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation DeepSigns: An End- to-End Watermarking Framework for Ownership Protection of Deep Neural Networks,

Reference 13

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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=2026-08-10T22:10:36.435943Z digest=sha256:78af6028e7cbdbdefe27ab4934dd21cad44a33244762a12e9e47f20f194556e0

Observation 9f8e2758-5e0c-4fe3-8de0-733330d65aa9 · outbound

This paper cites BadNets: Evaluating Backdooring Attacks on Deep Neural Networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation BadNets: Evaluating Backdooring Attacks on Deep Neural Networks,

Reference 14

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raw_fallback, observed 2026-08-10T22:10:37.243463Z

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=2026-08-10T22:10:36.444660Z digest=sha256:d3ed821039012cb6a874d64094f72045b8678d1cb3ddbf60ee1923791f6618dd

Observation d80493aa-43bd-4861-b551-e7fa8db6fb1c · outbound

This paper cites Backdoor Learning: A Survey,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Backdoor Learning: A Survey,

Reference 15

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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=2026-08-10T22:10:36.452550Z digest=sha256:fa51df187fd8cac615cd1937a8d9b98960e6fa0e681e06b880541afb8697a598

Observation 60521784-f4cd-4a84-aede-e25148c04538 · outbound

This paper cites Protecting Intellectual Property of Deep Neural Networks with Watermarking,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Protecting Intellectual Property of Deep Neural Networks with Watermarking,

Reference 16

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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=2026-08-10T22:10:36.458238Z digest=sha256:d1e54b2a3e675b2490c191eabb36c733a329881d13201e474beb93cb44e12663

Observation 0d7694b8-afa2-4aef-9668-50297f9393cc · outbound

This paper cites Adversarial frontier stitching for remote neural network watermarking,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Adversarial frontier stitching for remote neural network watermarking,

Reference 17

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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=2026-08-10T22:10:36.465141Z digest=sha256:242a4717ac4fcc9004c6f1ade3c35b69087d7ae39e968d77f13589f60ad3df99

Observation 301d25ad-0acf-4cca-ac91-6b36cf515ba4 · outbound

This paper cites ROWBACK: RObust Wa- termarking for neural networks using BACKdoors,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation ROWBACK: RObust Wa- termarking for neural networks using BACKdoors,

Reference 18

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:10:36.473873Z digest=sha256:0c8c73f0c9b729d84623a1d7b3515a76faf8059986282238fb023785e063f460

Observation 67629d85-4fc2-44ef-877c-77c81bae6e4e · outbound

This paper cites Explaining and Harnessing Adversarial Examples,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Explaining and Harnessing Adversarial Examples,

Reference 19

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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=2026-08-10T22:10:36.479410Z digest=sha256:3df1b407fb6d60fbe0b2e669405773a5b203359d2c224c443dbaa087fe0b3fdb

Observation ca1f3d00-1553-4433-beec-c6f30968a825 · outbound

This paper cites Certified neural network watermarks with randomized smoothing,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Certified neural network watermarks with randomized smoothing,

Reference 20

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no resolver link, observed 2026-08-10T22:10:36.486469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:36.486469Z digest=sha256:0de8590798ce635b6c34cad2e125985aaee54e2c01592344d5d98bbbb69de823

Observation 45d2fdb6-9678-432e-ae77-c1f5039c1124 · outbound

This paper cites Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing,

Reference 21

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raw_fallback, observed 2026-08-10T22:10:37.117046Z

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=2026-08-10T22:10:36.493301Z digest=sha256:2925043977ea1acf94bb08e4b7050ff459a70e19c404cb2b0ecefb6c92cb6a19

Observation f9902528-f84e-4364-a90e-81937f97653d · outbound

This paper cites Entangled Watermarks as a Defense against Model Extraction,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Entangled Watermarks as a Defense against Model Extraction,

Reference 22

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raw_fallback, observed 2026-08-10T22:10:37.098275Z

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=2026-08-10T22:10:36.500553Z digest=sha256:9363f130aaa379066ac7ef9df22d3ea3213d1b84d88677fed640ff468de15277

Observation b0b93197-a432-4355-9888-50854ee33d6e · outbound

This paper cites Towards Robust Model Watermark via Reducing Parametric Vulnerability,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Towards Robust Model Watermark via Reducing Parametric Vulnerability,

Reference 23

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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=2026-08-10T22:10:36.505862Z digest=sha256:24e766ebc1ee81ca35dc14c3b9c26e37f951c9662a00dbbed7cc5decb5268641

Observation cfa41377-ddaa-46ce-ba78-1c6146aafed1 · outbound

This paper cites Free Fine-tuning: A Plug-and-Play Watermarking Scheme for Deep Neural Networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Free Fine-tuning: A Plug-and-Play Watermarking Scheme for Deep Neural Networks,

Reference 24

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raw_fallback, observed 2026-08-10T22:10:37.061303Z

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=2026-08-10T22:10:36.511306Z digest=sha256:8e0dc3548bf26e29ef67e0833f745864ab839a2ca22e7a6a71a16858f4e09a45

Observation 7893d9cf-5f04-49db-a14d-6342387032f4 · outbound

This paper cites Cosine Model Watermarking against Ensemble Distillation,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Cosine Model Watermarking against Ensemble Distillation,

Reference 25

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raw_fallback, observed 2026-08-10T22:10:37.040388Z

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=2026-08-10T22:10:36.517281Z digest=sha256:d918cc50b9056ed232fa2fa835366113c970d5c7a65e8f9526c1c398bbacdcc3

Observation 8ee05e90-751a-48bb-a2f1-c45c444824e0 · outbound

This paper cites Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copy- right Protection,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copy- right Protection,

Reference 26

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raw_fallback, observed 2026-08-10T22:10:37.013220Z

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=2026-08-10T22:10:36.522340Z digest=sha256:052ffb72abb3d7a6fab25d1bd84e24b951cfd36e3e34d4b6fd19b742f9a7c7a0

Observation 84b2ea9e-b5f4-4ec1-a247-cef03ba540c1 · outbound

This paper cites Unambiguous and High- Fidelity Backdoor Watermarking for Deep Neural Networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Unambiguous and High- Fidelity Backdoor Watermarking for Deep Neural Networks,

Reference 27

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raw_fallback, observed 2026-08-10T22:10:36.990692Z

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=2026-08-10T22:10:36.530628Z digest=sha256:d9de01bba422ff52ae6a9c43bccebb7991a348c16cab8d5ad1e4ca144b34afdc

Observation 1b9a0a46-d601-49dc-829e-b738675fc5b0 · outbound

This paper cites Watermarking Deep Neural Networks in Image Processing,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Watermarking Deep Neural Networks in Image Processing,

Reference 28

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raw_fallback, observed 2026-08-10T22:10:36.968414Z

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=2026-08-10T22:10:36.536017Z digest=sha256:c1ca2955ad0f6b3660c878def24f7c144faa1e43f267bd2b2664871992a9f771

Observation f14dd3e9-0f24-412b-b938-aac4db1386c1 · outbound

This paper cites A Black-Box Watermarking Modulation for Object Detection Models,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation A Black-Box Watermarking Modulation for Object Detection Models,

Reference 29

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raw_fallback, observed 2026-08-10T22:10:36.935294Z

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=2026-08-10T22:10:36.541972Z digest=sha256:e43dfdef6c788d713a449a8a3c50df10eac40dafa18b47a05d11e90d4987402c

Observation 9d299aa9-e6e6-4106-8268-934745e817fc · outbound

This paper cites Catastrophic Interference in Connec- tionist Networks: The Sequential Learning Problem,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Catastrophic Interference in Connec- tionist Networks: The Sequential Learning Problem,

Reference 30

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raw_fallback, observed 2026-08-10T22:10:36.908320Z

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=2026-08-10T22:10:36.547700Z digest=sha256:de3d1e48096e80a81ac6b27a70df8acd82603864a3d93285e6245d3fbc5f9798

Observation 7c6a4b10-35e9-43f6-89b9-64a632c2d2b7 · outbound

This paper cites Compete to Compute,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Compete to Compute,

Reference 31

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raw_fallback, observed 2026-08-10T22:10:36.880062Z

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=2026-08-10T22:10:36.552981Z digest=sha256:ae99e355665b439a42d1cba2ea3db3f426d87ae8b829d197e88ccfb5bfea3509

Observation 1f9f2c22-01a6-4883-9bdb-bf5cddea1f45 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Overcoming catastrophic forgetting in neural networks,

Reference 32

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raw_fallback, observed 2026-08-10T22:10:36.857915Z

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=2026-08-10T22:10:36.559345Z digest=sha256:c89ec199babc23c3086220c1d4c87e7348384cb763d97f1ddf74f9b24662080a

Observation 0adac29f-2bf9-4a9b-8aa2-645ded8713a7 · outbound

This paper cites Ensemble Learning in Fixed Ex- pansion Layer Networks for Mitigating Catastrophic Forgetting,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Ensemble Learning in Fixed Ex- pansion Layer Networks for Mitigating Catastrophic Forgetting,

Reference 33

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raw_fallback, observed 2026-08-10T22:10:36.835911Z

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=2026-08-10T22:10:36.567246Z digest=sha256:0b65268f36692eb794c43331bcfd577a1950ec6c6a73bcc54b97f92a32e3a5e0

Observation 9b968c9e-76a5-4ddf-bde7-09df024cf69a · outbound

This paper cites Measuring catastrophic forgetting in neural networks,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Measuring catastrophic forgetting in neural networks,

Reference 34

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raw_fallback, observed 2026-08-10T22:10:36.810521Z

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=2026-08-10T22:10:36.574267Z digest=sha256:9d0046f74ccb98ba08b4954dfd3c6d49703e449a97e8f6986baa53867cc53bfd

Observation 306f98b3-7edd-4f6b-b08d-24892d886966 · outbound

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

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Learning multiple layers of features from tiny images,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T22:10:36.579703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:36.579703Z digest=sha256:fc7819e713bf6cbb8f1ef9e33effc766bc7e2b5944b79a9a326c0c910b763686

Observation 8dfc19ac-a951-4983-a2d4-7be2f4b49f01 · outbound

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

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Reading digits in natural images with unsupervised feature learning,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T22:10:36.585689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:36.585689Z digest=sha256:eaaaedd054dee40bf2e1f252a9110b6b7a40974ce47a26a010438545910fbc3c

Observation fee48e05-9d3a-45f7-9a49-e6761ec0e296 · outbound

This paper cites Deep Residual Learning for Image Recognition,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Deep Residual Learning for Image Recognition,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T22:10:36.592169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:36.592169Z digest=sha256:7e7550fdee00e24be33b77b5b263dc27d55cb924944606e24549b29b12d5c0c2

Observation 091fdb3e-8871-4eff-be17-248c44bbe4f0 · outbound

This paper cites An Image is Worth 16x16 Words: Trans- formers for Image Recognition at Scale,.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation An Image is Worth 16x16 Words: Trans- formers for Image Recognition at Scale,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T22:10:36.598133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:36.598133Z digest=sha256:44683c14067c5f19781ce9e717ddf0b9fbd1fb4b0500d22b0adc67d4dddd1378

Observation 244924cd-1378-4d4d-b522-f671961044fb · outbound

This paper cites SoK: How Robust is Image Classification Deep Neural Network Watermarking?.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation SoK: How Robust is Image Classification Deep Neural Network Watermarking?

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:10:36.707928Z

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=2026-08-10T22:10:36.604255Z digest=sha256:9cb7c43842b233bc277c5cd40cd012d1ca5d5781579b8cb5de94dea28a67a0c4

Observation ef2e456c-5436-4362-a749-323c664cf9bf · outbound

This paper cites Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation

Reference 40

Resolution
metadata mismatch
local_arxiv, observed 2026-08-10T22:10:36.670211Z

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=2026-08-10T22:10:36.611106Z digest=sha256:0c98bf3a816fd3c5c9fc001ea04aea3de974054769b47485137bd03c4d9ec296

Pith citing papers

Observation ef2e456c-5436-4362-a749-323c664cf9bf · inbound

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation cites this paper.

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation

Reference 40

Resolution
metadata mismatch
local_arxiv, observed 2026-08-10T22:10:36.670211Z

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=2026-08-10T22:10:36.611106Z digest=sha256:0c98bf3a816fd3c5c9fc001ea04aea3de974054769b47485137bd03c4d9ec296