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Paper Citation Record · LEDGER

TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1908.01763.

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

pith.paper-citation-record.v1
1908.01763 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:58:07.266216Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T19:56:11.282031Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 41a05183-14ee-48d1-8f00-ac4f2e1ba8d7 · inbound

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics cites this paper.

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:48:47.581951Z

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=pdf_text observed=2026-05-24T02:46:59.823305Z digest=sha256:be18608955636aa20301fe7d4f8478bb348afe2f9dfa50c4a933152f846931f5

Observation 2bc63cf0-9ee8-44fc-8664-0feab63fafb5 · inbound

DeTrigger: A Gradient-Centric Approach to Backdoor Attack Mitigation in Federated Learning cites this paper.

DeTrigger: A Gradient-Centric Approach to Backdoor Attack Mitigation in Federated Learning TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:58:17.109700Z

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=pdf_text observed=2026-05-23T17:57:17.355234Z digest=sha256:17cecaca3888dd8fea73989675420a0113c1f006240e5897987bb26dfdfe834a

Observation ed4b9740-85bf-4bfb-96f6-1771e2c9f968 · inbound

InverTune: Removing Backdoors from Multimodal Contrastive Learning Models via Trigger Inversion and Activation Tuning cites this paper.

InverTune: Removing Backdoors from Multimodal Contrastive Learning Models via Trigger Inversion and Activation Tuning TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T00:58:07.266216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:07.266216Z digest=sha256:1e406e036a54e88c3f6a117b11eeda985e2edff8595da537d24d1707c0b5de7d

Observation 76d91001-a3f6-4954-a453-900ac11b2e6d · inbound

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey cites this paper.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-04T22:06:30.346108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:06:30.346108Z digest=sha256:273c866f5d2842f6ac447de2560ffa0772e02aab7c369e71bb171d0a83e13263

Observation 6ff0ca1a-a84e-468e-985c-f5f4aa8d963f · inbound

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions cites this paper.

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:11:12.625487Z

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=pdf_text observed=2026-05-08T17:50:49.951655Z digest=sha256:baefc9824e6eb0613548f8b9ac8c6a791311d2c5f3796880ed5d1ad6c5f354aa

Observation ff007591-ce36-4c93-9516-77a01668e54b · inbound

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions cites this paper.

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-12T17:35:56.649298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T17:35:56.649298Z digest=sha256:e43e25439ef064b3aace8def66700bc7a8c530d5b2a38cdc10aa89322b81e805

Observation 695fa47c-149b-4249-85d0-b2c82c05dd48 · inbound

Detecting Trojaned DNNs via Spectral Regression Analysis cites this paper.

Detecting Trojaned DNNs via Spectral Regression Analysis TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T04:03:56.625899Z

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=pdf_text observed=2026-05-21T04:03:36.586890Z digest=sha256:57a8581b2f515695a445b36058025deff1182ba674c6e32e7ee9c0ee88cb8141

Observation 12a0e800-757f-489b-97ed-459b229176e7 · inbound

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning cites this paper.

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-01T19:56:11.283546Z

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=pdf_text observed=2026-06-28T21:52:23.150188Z digest=sha256:2d32affbc7d48db4c4ef6be0eb8d8df7216c687d7babddf0b3ebde018cc799b1

Observation 8b47b2ad-6416-4183-817b-59fe26216511 · inbound

Triggering Stealthy Feature Map Backdoors via Physical Fault Injection in Embedded Neural Networks cites this paper.

Triggering Stealthy Feature Map Backdoors via Physical Fault Injection in Embedded Neural Networks TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 55

Resolution
unresolved
no resolver link, observed 2026-07-13T02:46:49.236604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T02:46:49.236604Z digest=sha256:50bb30ed2aaa850a879746691598f305cd00a397d241b0dd519e8a2eacbf9038