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Paper Citation Record · LEDGER

Diversifying the High-level Features for better Adversarial Transferability

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2304.10136.

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

pith.paper-citation-record.v1
2304.10136 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:54:01.870256Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T00:25:48.573422Z

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 e6b6ba24-ec7f-4766-bce4-f58980f670c7 · inbound

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving cites this paper.

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving Diversifying the High-level Features for better Adversarial Transferability

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-23T16:35:42.100179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T16:35:24.063578Z digest=sha256:dad2c7259f091f091eecf632f7325833a340780b5f6bcb9764d971f4b4bad0e8

Observation ff4722eb-dce9-4b1f-9438-5983a992cdc6 · inbound

CogMorph: Cognitive Morphing Attacks for Text-to-Image Models cites this paper.

CogMorph: Cognitive Morphing Attacks for Text-to-Image Models Diversifying the High-level Features for better Adversarial Transferability

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T17:54:01.870256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:54:01.870256Z digest=sha256:9b333289e7ae4f9da787bd42ab1c24bd6159cdc4626572b8d40691fdb02bc1a8

Observation 8520eb34-ca97-42d2-ac8b-24281697b944 · inbound

Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving cites this paper.

Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving Diversifying the High-level Features for better Adversarial Transferability

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:07.937330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:55:07.937330Z digest=sha256:6cb0c512837e3e918ff4e4de6405ec26cdbe0197128374983f4e906bf135831c

Observation 5135d18b-d3b8-4681-9fbf-d89173971a9d · inbound

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models cites this paper.

A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models Diversifying the High-level Features for better Adversarial Transferability

Reference 78

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T22:05:49.270863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T20:14:02.553313Z digest=sha256:7f4e57024449ae9189718aadb02d44c8e97959f7c0ddbd43e286fc09aefc72c6

Observation ae9f9671-d2d8-4cec-b76d-162b335f9f7e · inbound

Multimodal Backdoor Attack on VLMs for Autonomous Driving via Graffiti and Cross-Lingual Triggers cites this paper.

Multimodal Backdoor Attack on VLMs for Autonomous Driving via Graffiti and Cross-Lingual Triggers Diversifying the High-level Features for better Adversarial Transferability

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T21:55:49.655036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T20:30:29.032353Z digest=sha256:30bbd90d6e2e0d38cf3672e793f396370b2d91d0d6957f9460da27177440262d

Observation a753f844-e4bc-4c6d-8ac1-9679c586b78f · inbound

WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents cites this paper.

WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents Diversifying the High-level Features for better Adversarial Transferability

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:15:22.155129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-25T05:14:59.444339Z digest=sha256:d9b8efe412ef354ff94d29724c9b924e92be31bd5afa3b95ef344268ec55962a

Observation 39387ead-628b-4577-b642-37e0c5178ff8 · inbound

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective cites this paper.

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective Diversifying the High-level Features for better Adversarial Transferability

Reference 84

Resolution
verified exact
local_arxiv, observed 2026-07-09T00:25:48.576297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-09T00:16:03.334057Z digest=sha256:05c6c65276a8ec502fe8c1ba68756e8a7f7653a995250e86f10930c3692819ec