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Paper Citation Record · LEDGER

Intriguing properties of generative classifiers

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2309.16779.

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

pith.paper-citation-record.v1
2309.16779 v2

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 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:56:40.525123Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:30:33.593150Z

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 abd36027-19ad-4993-b428-6702596c6bbc · inbound

Illusion3D: 3D Multiview Illusion with 2D Diffusion Priors cites this paper.

Illusion3D: 3D Multiview Illusion with 2D Diffusion Priors Intriguing properties of generative classifiers

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T16:56:40.525123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:56:40.525123Z digest=sha256:31313f6ce2fd2358309cf28023601d2e75ad37a044d375cec7ac093f4630409e

Observation 554cc24b-a1fb-4947-91b1-b5519e8651d0 · inbound

Compositional Scene Understanding through Inverse Generative Modeling cites this paper.

Compositional Scene Understanding through Inverse Generative Modeling Intriguing properties of generative classifiers

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T13:31:06.162857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:31:06.162857Z digest=sha256:f03dabb5f459912d844f954aab0506aac7484b4bda16359ed9dcbbc9c851c907

Observation e282aa60-062c-4069-b8c5-93240bb5386a · inbound

Diffusion Counterfactual Generation with Semantic Abduction cites this paper.

Diffusion Counterfactual Generation with Semantic Abduction Intriguing properties of generative classifiers

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:30:33.595976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T05:30:32.925776Z digest=sha256:3141ec126b6a457a6ada82cd4a3b6e2063089335f12c7d42f50e057e073d94ec

Observation a40b7695-9883-420e-bea1-31ce17c58315 · inbound

Leveraging Prior Knowledge of Diffusion Model for Person Search cites this paper.

Leveraging Prior Knowledge of Diffusion Model for Person Search Intriguing properties of generative classifiers

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T12:52:07.490679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:52:07.490679Z digest=sha256:f66dbf35af00d2b049b61d48210f48e433ae8da810764d656ef9785403cd6d53

Observation c43937b5-7a78-4597-b0e1-4504fcfabb77 · inbound

Revisiting Autoregressive Models for Generative Image Classification cites this paper.

Revisiting Autoregressive Models for Generative Image Classification Intriguing properties of generative classifiers

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-13T22:10:29.821610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T22:10:29.821610Z digest=sha256:75a4f67c94f7233e2df8f8e511a3e33cf7bfb8a011250b9618434443679d23b9

Observation 0591156f-052a-4ef8-ba15-9b74ec50aef1 · inbound

Denoising Models Develop Human-Like Perceptual Illusion Representations Across Architectures cites this paper.

Denoising Models Develop Human-Like Perceptual Illusion Representations Across Architectures Intriguing properties of generative classifiers

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-01T18:58:30.406039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:58:30.406039Z digest=sha256:1c5f6aea508ed820d161fb792547f4dd11b2748ba3c99c7fc463e6668d1c7521