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Paper Citation Record · LEDGER

Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2411.19117.

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

pith.paper-citation-record.v1
2411.19117 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:29:52.362882Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:29:29.869414Z

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 43ffdd1b-5d53-4c42-b374-baea451a00f3 · inbound

Enhancing Self-Supervised Talking Head Forgery Detection via a Training-Free Dual-System Framework cites this paper.

Enhancing Self-Supervised Talking Head Forgery Detection via a Training-Free Dual-System Framework Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:51:30.394710Z

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=2026-05-08T01:23:27.355803Z digest=sha256:5ee59ab404497aa892cb038a79268ec90a10cf7b6191c5303f734b11be647e41

Observation 481dd4d7-3ee7-4a04-acac-96c7afdd0ac7 · inbound

Intermediate Representations are Strong AI-Generated Image Detectors cites this paper.

Intermediate Representations are Strong AI-Generated Image Detectors Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:56:06.702699Z

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=2026-05-08T16:55:44.000342Z digest=sha256:b3a87315b5c51989cbca0c4563d933464b4e0efedf4a22974d7bc7cb3e65d64d

Observation 1e6412db-ba6b-492e-9306-a4da1a9ab413 · inbound

HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection cites this paper.

HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-06-29T18:53:51.139775Z

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=2026-06-29T18:51:53.451225Z digest=sha256:50182ef75d79bff01658fe14cda097306c37c95182fa09e431ad2f9e993eda36

Observation 94078e66-9f0b-44b8-8245-3ce059e380c5 · inbound

DRIFT: From Robustness Gaps to Invariance Manifolds for AI-Generated Image Detection cites this paper.

DRIFT: From Robustness Gaps to Invariance Manifolds for AI-Generated Image Detection Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:37:09.173685Z

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=2026-06-27T22:33:47.940072Z digest=sha256:d15b85230846f061276c95597617a921e1847b1972e052038bc7f621a01a4084

Observation be25e0b6-4010-4c97-8af2-6c7555abe5d9 · inbound

How Fragile Are Training-Free AI-Generated Image Detectors? A Controlled Audit of Score Direction, Preprocessing, and Compression cites this paper.

How Fragile Are Training-Free AI-Generated Image Detectors? A Controlled Audit of Score Direction, Preprocessing, and Compression Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:29:29.873189Z

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=2026-06-26T18:03:36.063596Z digest=sha256:df104b9fdb9dae26bbbd25f3b74eed54d401c0cc6f22145b81fa94d6e5e3d983

Observation 2bf48227-4e13-4905-9765-a52dfbe035a7 · inbound

GLID: Gated Local Intrinsic Dimension Repairs the Blind Spots of Face-Forgery Detectors cites this paper.

GLID: Gated Local Intrinsic Dimension Repairs the Blind Spots of Face-Forgery Detectors Understanding and Improving Training-Free AI-Generated Image Detections with Vision Foundation Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T14:29:52.362882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:29:52.362882Z digest=sha256:8bfd7ed2aacc81e0ff20d5a41b0eb1be543c27ccd82406132317e7b7db4d113a