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Paper Citation Record · LEDGER

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning

As of 9 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2508.05404.

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

pith.paper-citation-record.v1
2508.05404 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:24:05.310742Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved40
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cf9ecc33-9232-44d9-92ab-7ee498607b92 · outbound

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

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:03.228270Z digest=sha256:3a4bcc23645ba017a0d3ca338035832162be060e755ff00d5b6bd1afece6169f

Observation cceba70b-4e20-4123-adc1-07daf8a370ba · outbound

This paper cites Distilling the Knowledge in a Neural Network.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Distilling the Knowledge in a Neural Network

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:03.261013Z digest=sha256:4be279ea8d55aafabc7936e391fddbcc77d00242c7d3d87e9ce531b8d3b6b779

Observation c6cf34c1-32a0-4e95-a0fc-623fb3cfe3ba · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:03.339328Z digest=sha256:d1c564a8df28d966503d0964c6a7c3f955f45a02cc184cb7c6e816705e4aae57

Observation 84ae4f14-53d6-4d1d-b04a-b1df7c024c07 · outbound

This paper cites Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:03.420014Z digest=sha256:ad9ec75bbfb5c3589dc512515716330a4c68a1fd8c9be67e3932f1b54e92b7b3

Observation 5d776407-131a-4873-82ec-1c7aad29aaa2 · outbound

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

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:03.476827Z digest=sha256:fa91af27ab8897cbc6af8c57fa3736ecd23fe3ee1639b739b8f1610d161a5a82

Observation 24a6079f-2e71-4ad3-90e9-d978aa87763e · outbound

This paper cites WaNet -- Imperceptible Warping-based Backdoor Attack.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning WaNet -- Imperceptible Warping-based Backdoor Attack

Reference 6

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no resolver link, observed 2026-08-05T23:24:03.567013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:03.567013Z digest=sha256:890cb697f30328ddf8dc3d6c78391693921cb30b63f91424ce30f85bc1149b8c

Observation 14efb9be-c45e-459c-afb8-a4281c8759eb · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 7

Resolution
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raw_fallback, observed 2026-08-05T23:24:05.878088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:03.652840Z digest=sha256:7f9671051fcca86f722ce45b0b216db6ed30d632ec6c701ecd6008ae79fdd520

Observation eb199a9c-e0c3-4fc2-8e44-4d1516d1f541 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:03.735553Z digest=sha256:b37f96ecd997775bd84d888d246492b801c9380783bfbbefb66470629871b877

Observation 164041cd-a0fa-46ed-a6e7-aeb5e5b69a81 · outbound

This paper cites Label-Consistent Backdoor Attacks.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Label-Consistent Backdoor Attacks

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:03.801970Z digest=sha256:2560a53f3d1c5121db177e6f90ae0c962163fd1f4505c469521e1567a44c3e6b

Observation b26b0d5f-497a-47ad-b1e4-e3c6f8670da9 · outbound

This paper cites Barni, K.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Barni, K

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:24:05.857127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:03.899808Z digest=sha256:9b284c7ba096770075a63b937862b39119daeb895605e3fdf271863a6fe5b893

Observation 4866b808-5ba9-4a42-8b05-442f787a30ea · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:03.980180Z digest=sha256:f9b69467c95a93bfe49604c8f7248c2b0a3ceebbae00294b3666f23147dda8f5

Observation 5a128b3c-56d2-4cc1-a5ad-a2c2af8f5529 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.054466Z digest=sha256:15866922845a5b8f4dfc33a51f2f5beefeb97864de1c2c8cc6494b3d6aebb447

Observation 20f5cfe1-c749-4cf5-9f5f-8d8072340fb3 · outbound

This paper cites Label Refinery: Improving ImageNet Classification through Label Progression.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Label Refinery: Improving ImageNet Classification through Label Progression

Reference 13

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source=arxiv_source observed=2026-08-05T23:24:04.143167Z digest=sha256:8d14e0b2bcc70b075e7474ec40645629cca6f366776e8ee05c095d6fcf6343ef

Observation cd64d2ad-0829-4dda-baa5-3f250af11a1d · outbound

This paper cites Krizhevsky, G.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Krizhevsky, G

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:04.146630Z digest=sha256:a3473160431d19de8fc2c60da0423930749c466c7d1ebe8cc6c37aea25bca114

Observation 9228ea17-a1c0-47ad-99f4-e0f2dc3226a6 · outbound

This paper cites Stallkamp, M.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Stallkamp, M

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.149776Z digest=sha256:b52bfcb09506ace30a68277a86c82f046ad172eeb06f341f09333ea6a6b7c685

Observation 5b23f822-ddbf-43d0-8aae-5bdbf9e40c6a · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.155438Z digest=sha256:dd52bba6d1b4c7a541f4522065842d3198ef45481be2e577a15724fd08334536

Observation 8587f822-66cd-45ea-9520-ba0deb2a4116 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.267557Z digest=sha256:16b9e607f6f0d33f496aafa7f54fa80d2f0039a121dfe7d65b3958e671c64dfc

Observation 8420c489-9cfc-4025-b1ec-91fc1fd04aa3 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.336857Z digest=sha256:a4c74a4c3e73202397400e3cb8e1f66b53b9e77275b0d9ffcbb1b7343af2d549

Observation f33e54b4-c4cc-4b43-9043-089e9cf153ae · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.413857Z digest=sha256:6e9988dae4cf1221e37daed95c01b46d24a7aa4c8095ce87877edeed33d2be69

Observation 68a2330b-110f-40f2-81f5-99dd95dc0799 · outbound

This paper cites Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 20

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-05T23:24:04.443794Z digest=sha256:a26b85d1b9c191e6a634aad35a2c89a6d5aa1d52db127143131c48c8b71bd7b7

Observation 4f5f66b0-c20e-4b9c-b006-fd0ad3b54363 · outbound

This paper cites Backdoor Defense via Decoupling the Training Process.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Backdoor Defense via Decoupling the Training Process

Reference 21

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-05T23:24:04.556438Z digest=sha256:8f18c712a03e34a9044528a6a6a9d17609bf4c0e3a5cab17840d5afc99c138fd

Observation 1df41d4d-2306-4c95-9e8e-40deecac403b · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.678976Z digest=sha256:6e353ebea5c7241c495180b10db38f494ce3121154c0aa00207e4dc4ec752f86

Observation 680f5888-18b2-4ab4-8cfa-fd351a8df327 · outbound

This paper cites Udeshi, S.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Udeshi, S

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.789383Z digest=sha256:dcd9ea4726ad8a19a6a5a1b83c79f3636289c4480ec03bd4e12a6e17a882bed8

Observation bab4564f-b90d-43d9-8099-ccf2e1879ce1 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:04.905291Z digest=sha256:2820666a3ff70bec9fd871ceb9a4b9a95ef1594a66cb2dea3323005d92e731f7

Observation 73547c01-8b65-4881-a145-d68c11287443 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.049908Z digest=sha256:1005fb3d1ebdefa472494a6a3e8091dff3b32bfe9314d09ce31bfd7d281b29a4

Observation 6a217c6e-5d81-4377-a416-4ae69d700a56 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.197607Z digest=sha256:b815d3934df9a957749fd676f600d23d1c56d0ec8a8f11f53e641889238a9d93

Observation e96809b1-8350-46b2-9ef1-d69bdb7666ae · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.254492Z digest=sha256:53719a032f2bd38e61c93f6626353c1d9807e4ac141c65d8c454d1be9f73f080

Observation d255de45-7389-4303-9b59-1e241b7a22ff · outbound

This paper cites Wu and Y.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Wu and Y

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.258116Z digest=sha256:0fc131faa59b4fddaa636a59c1577401118cbe3dd4345c774ea32a2a091fbda3

Observation f8789087-8ff7-4b31-aca7-62252c9a1b91 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.261032Z digest=sha256:58e2e20e74bab91cf5108cc3c4f4f96cd78690114bd5c2c5a5924078c4026a05

Observation 45275bd6-4edf-47db-b5ff-ee304687ff06 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.264156Z digest=sha256:9adc7e1a773431236c2810c7067d4739b3d10112e1639cbb658399426ffb88be

Observation 760415a3-a482-471e-9173-b23cbbe25553 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.267119Z digest=sha256:f6683d17716c621483d9c51101c09c480e0b4ad64e867a9c4b0af87af0302422

Observation 222682d7-eb42-41d8-b29e-8de46696189d · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.269889Z digest=sha256:6ba6bf3416da862f50787a49f0eca779368a71ab1ec26782552903e2372c809c

Observation b925c3ec-1770-4e3e-93eb-a26e87eaa840 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 33

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raw_fallback, observed 2026-08-05T23:24:05.660570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.272671Z digest=sha256:5dfccac38cc9a759d8cff891b2e89b7b4765ec0c78467a2d091aa95d575bf75b

Observation 63c22160-5e2d-413b-bee0-bd1135916155 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.275446Z digest=sha256:3568f83ecd62e5020f45f5a78e6444cbe964b55058f1d3cc46bc670806a511bb

Observation d7c32960-5cb6-44a2-aad4-2c65d6b887d3 · outbound

This paper cites FitNets: Hints for Thin Deep Nets.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning FitNets: Hints for Thin Deep Nets

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:05.278365Z digest=sha256:9db0f9bc8deac48ceb698ee80447a3a9f9e740693d94412626d0e9db3400c215

Observation 69a44137-d89c-4a29-bf5b-edf7974dadd6 · outbound

This paper cites Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer

Reference 36

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no resolver link, observed 2026-08-05T23:24:05.281446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:05.281446Z digest=sha256:8ca92d53da0db6c6840b79a8ed48a8b52f8cba3f47fd9f78d45d3727e472bc9c

Observation fac7eb9c-760b-4170-b033-5101918f3631 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-05T23:24:05.640113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.283944Z digest=sha256:8f6ab316ae81c1d1450edf0b0bb744dc47138902607e8c6468ef2450a2cca2db

Observation ae70889f-9809-4a47-ac67-2b4f42c0da31 · outbound

This paper cites Zhang, T.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Zhang, T

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:24:05.630057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.286579Z digest=sha256:2182e4b4dbd3217809f8eea89b3145b816e2c3e53666b40b3b3725ef226b6063

Observation ce7d5e8d-dc11-4f83-8679-615befc35d19 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-05T23:24:05.619589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.289077Z digest=sha256:264eccfbb786f1f42ca7b03a5d827ebcfebe425c0c0f586ec1da1d51de3a8b8c

Observation 5c36846c-d052-4c7a-aff4-181290131225 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-05T23:24:05.607233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.291831Z digest=sha256:7ae4abe950298f2528e2fcc6fdf1a347bedfaa12511d3d7d3efb05960d6e922d

Observation d94068db-bd9f-41e1-b71c-c6b86ad0de28 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-05T23:24:05.595455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.294353Z digest=sha256:5cf94ab316ccb7b18dd00c7852f4c5620f4e1d4621d7db359dba8510649c0c07

Observation b025c6b4-7a57-4e6b-b34f-f90a267ce699 · outbound

This paper cites Zhang, J.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Zhang, J

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:24:05.584491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.297223Z digest=sha256:6b1b6b69f941dae0ed524d270ed27fcc87f3314e18c6fb3bd9755e33e6e25f6e

Observation 303f81e1-bd7e-4386-98f2-9c7bc2934708 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-05T23:24:05.573424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.299854Z digest=sha256:90fa3936aef2ed0efb19c8df25d0c2c7df666b78a8f3aae66ba1b49fe13dfaef

Observation 73ffe036-830c-4eb0-949c-da7c555786f3 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-05T23:24:05.562101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.302653Z digest=sha256:0065679308aa4cd5fa92be11a73c0d0854e189bbcdebe3fb7d20c62b73f47999

Observation a2ba7aaa-d11d-4777-8447-00b72e2bff92 · outbound

This paper cites Van der Maaten and G.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Van der Maaten and G

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T23:24:05.305693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:24:05.305693Z digest=sha256:dc793b1f40998e2402ed0171b21bd632788c817185f37c63d521ec9e5102f1bd

Observation 7a1853a7-2565-4c85-bcdd-1de1fa337553 · outbound

This paper cites an unresolved cited work.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-05T23:24:05.545794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.308209Z digest=sha256:9c99a745c4804b14603ab06bce115e7034d97d5755a16e34c703109e13feeb39

Observation d4f6a6e1-cadc-4277-b434-37e6671de8bf · outbound

This paper cites Akiba, S.

NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning Akiba, S

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:24:05.534826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T23:24:05.310742Z digest=sha256:c928a828995d94a7c62fe8d69f54b26486655a92aa714caf51e9bdf06ca5c6bf

Pith citing papers

No inbound Pith citation observations are available.