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Paper Citation Record · LEDGER

Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2406.18844.

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

pith.paper-citation-record.v1
2406.18844 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:45:19.848875Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:36:17.857027Z

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 e98241a9-ae05-4ef6-813d-ab660bd90d11 · inbound

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety cites this paper.

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 295

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:42:33.930609Z

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=pdf_text observed=2026-05-23T04:39:04.591722Z digest=sha256:df29bce381b001b2b3cf63a0f0c25425f22cd80fe9c81fd3f9a78daff4a796c3

Observation c4beee14-534b-4782-86c2-fa82b65edf46 · inbound

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations cites this paper.

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 127

Resolution
unresolved
no resolver link, observed 2026-08-07T19:45:19.848875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:45:19.848875Z digest=sha256:62162dbca53a88baaf4e69040e0eeef31dc41fbbcb0d86c5b4c6b4ad2337650a

Observation 24f83c2e-78df-41c0-ba74-c7b9988f8f20 · inbound

Three Minds, One Legend: Jailbreak Large Reasoning Model with Adaptive Stacked Ciphers cites this paper.

Three Minds, One Legend: Jailbreak Large Reasoning Model with Adaptive Stacked Ciphers Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T15:08:11.420034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:08:11.420034Z digest=sha256:29a03f8266e9b840775be09906f10862cd95e1bf594298ff69b053d39704cbff

Observation 615a5c13-2769-45a7-90b7-6efda48fc19f · inbound

BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization cites this paper.

BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:03:59.401319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:03:59.401319Z digest=sha256:978dc0666b202c3cbf8cf62d5aab9a67d1a45adb8b4303aa783d7de7fb939a37

Observation 902b8e0c-a290-4486-bdda-ed953b77ee00 · inbound

Backdoor Cleaning without External Guidance in MLLM Fine-tuning cites this paper.

Backdoor Cleaning without External Guidance in MLLM Fine-tuning Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:52.349818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:52.349818Z digest=sha256:cca3c55024ae85c6fe2e79c2e5f7797bf02641b85579e8a69ea9a74af73f1fcc

Observation fcd96ad3-c25e-4a25-aa05-89d835ff21d4 · inbound

AdInject: Real-World Black-Box Attacks on Web Agents via Advertising Delivery cites this paper.

AdInject: Real-World Black-Box Attacks on Web Agents via Advertising Delivery Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:46.499083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:46.499083Z digest=sha256:525f6d7fd24429e846e0fefe1c77fccfcf752f73e6ec6aa653bff135dc559c3f

Observation 18b3f355-f8f6-46e0-97db-9470e5b3e604 · inbound

Robust Anti-Backdoor Instruction Tuning in LVLMs cites this paper.

Robust Anti-Backdoor Instruction Tuning in LVLMs Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T11:07:37.411521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:07:37.411521Z digest=sha256:f4b9226ffe75157d0e85f705e5026c0f5a0e89dd61e75c442518ecdfe3730a72

Observation 6f46186f-673f-48bb-a3cf-67794586aeb1 · inbound

Poison Once, Control Anywhere: Clean-Text Visual Backdoors in VLM-based Mobile Agents cites this paper.

Poison Once, Control Anywhere: Clean-Text Visual Backdoors in VLM-based Mobile Agents Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:17.724760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:41:17.724760Z digest=sha256:e65e935e4ee67eeb3c7aad2cafcc5e4d110ef8df834c82439038e09ee5910160

Observation f2a464c6-72c3-4787-a361-7b7c52369bc6 · inbound

Multimodal Fine-grained Reasoning for Post Quality Evaluation cites this paper.

Multimodal Fine-grained Reasoning for Post Quality Evaluation Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:42:37.820899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:42:37.820899Z digest=sha256:c2a46e04f670c8ab7bd93376eaad66ed97e8ae6fe12a6f10f86aaed156f1cb92

Observation bb605fe9-7a89-46f3-afe7-111c1e163973 · inbound

TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models cites this paper.

TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-04T13:52:14.434954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:52:14.434954Z digest=sha256:813dac0a5bf9c44455d23da7947c6547e7032ec6b13f3bc7e2deaf4e7051f0b0

Observation f40de095-85d5-4756-b348-0912ab5e2d5e · inbound

TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning cites this paper.

TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:35:28.738550Z

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=pdf_text observed=2026-05-25T07:33:15.865358Z digest=sha256:6344e17dd80386be3ffa3bd7af6c922b22044503bcd1adad52a716a56b224f69

Observation c9add1b6-4b2b-4d13-b687-df10a64ff2d5 · inbound

BYORn: Bootstrap Your Own Responses to Defend Large Vision-Language Models Against Backdoor Attacks cites this paper.

BYORn: Bootstrap Your Own Responses to Defend Large Vision-Language Models Against Backdoor Attacks Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:36:17.858339Z

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=2026-06-28T15:10:18.936026Z digest=sha256:51dc97863542243669b92373aee9b9f5fe42adb6a16c91eafb3f13de66e59282