Paper Citation Record · LEDGER

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey

As of 19 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 3 inbound Pith citation observations for arXiv:2509.07504.

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

pith.paper-citation-record.v1
2509.07504 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:06:30.939408Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T21:55:21.464980Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T11:28:04.481664Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy2
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3d43d82-36aa-4a08-a3e6-63f72ee796f6 · outbound

This paper cites Twin Trigger Generative Networks for Backdoor Attacks against Object Detection.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Twin Trigger Generative Networks for Backdoor Attacks against Object Detection

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T22:06:31.251196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fae53a06-553d-41e2-8406-81334b9ae269 · outbound

This paper cites Test-Time Backdoor Attacks on Multimodal Large Language Models.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Test-Time Backdoor Attacks on Multimodal Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:30.759059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 689de4ec-8014-4fcf-9866-f90f10626039 · outbound

This paper cites Backdoor Pre-trained Models Can Transfer to All.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Backdoor Pre-trained Models Can Transfer to All

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T22:06:31.150127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a80bd4f1-c510-4b9c-8336-8e8744f069d3 · outbound

This paper cites InProceedings of the AAAI Conference on Artificial Intelligence, volume 38, 21850–21858.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey InProceedings of the AAAI Conference on Artificial Intelligence, volume 38, 21850–21858

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:31.568063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76b638e5-550c-45cb-ab96-746e2fafd12c · outbound

This paper cites Lu, D.; Pang, T.; Du, C.; Liu, Q.; Yang, X.; and Lin, M.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Lu, D.; Pang, T.; Du, C.; Liu, Q.; Yang, X.; and Lin, M

Reference 199

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:31.712998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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

This paper cites TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems.

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.

Observation 49054270-2e5f-447c-8195-13bd8347558f · outbound

This paper cites Backdoor Attacks on Pre-trained Models by Layerwise Weight Poisoning.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Backdoor Attacks on Pre-trained Models by Layerwise Weight Poisoning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:30.519979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e97473f-aba8-4531-987f-9e434916e590 · outbound

This paper cites Backdoor Attack through Frequency Domain.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Backdoor Attack through Frequency Domain

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:30.892675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 954ddab0-abca-4431-922c-d811d22c7901 · outbound

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

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:30.176645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4115fc25-3942-45d7-b6b6-a52cca6289e7 · outbound

This paper cites Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers

Reference 2023

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T22:06:31.058416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e42f754c-8f96-458b-a00b-f2403f7ac63b · outbound

This paper cites Megatron: Evasive Clean-Label Backdoor Attacks against Vision Transformer.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Megatron: Evasive Clean-Label Backdoor Attacks against Vision Transformer

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T22:06:31.369512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 20aa64e7-d081-4dc8-b2b9-f46b2b5a5f35 · outbound

This paper cites Prototype Guided Backdoor Defense.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Prototype Guided Backdoor Defense

Reference 2025

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T22:06:31.474018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97a4fd20-8b7b-4764-9585-f76648535994 · outbound

This paper cites Backdoor Defense via Decoupling the Training Process.

Backdoor Attacks and Defenses in Computer Vision Domain: A Survey Backdoor Defense via Decoupling the Training Process

Reference 4139

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:30.445063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation b800213f-5d5e-40cc-899b-3ddb7cd2453b · inbound

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks cites this paper.

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks Backdoor Attacks and Defenses in Computer Vision Domain: A Survey

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-14T18:39:22.325484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a198a014-46f7-4b1c-880c-045d532aa16b · inbound

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks cites this paper.

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks Backdoor Attacks and Defenses in Computer Vision Domain: A Survey

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.204378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 068a9414-0971-4065-b1df-7f6dabc78ba1 · inbound

Dummy Backdoor as a Defense: Removing Unknown Backdoors via Shared Internal Mechanisms for Generative LLMs cites this paper.

Dummy Backdoor as a Defense: Removing Unknown Backdoors via Shared Internal Mechanisms for Generative LLMs Backdoor Attacks and Defenses in Computer Vision Domain: A Survey

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T11:28:04.483125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.