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Paper Citation Record · LEDGER

A Reproducible Extraction of Training Images from Diffusion Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2305.08694.

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

pith.paper-citation-record.v1
2305.08694 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:11:18.255337Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T15:05:48.271303Z

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 ce7fc632-c11b-4c62-ac96-dd0f53601b73 · inbound

Finding DoRI: Discovery of Retained Images in Diffusion Models cites this paper.

Finding DoRI: Discovery of Retained Images in Diffusion Models A Reproducible Extraction of Training Images from Diffusion Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T15:11:18.255337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:11:18.255337Z digest=sha256:48bfa56daf26a8de717924591fd9e7a63b1a94502f35e0f70e5e58882ae7f4c8

Observation f3dbb0e6-1852-4114-8a3b-9608f8482720 · inbound

You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models cites this paper.

You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models A Reproducible Extraction of Training Images from Diffusion Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-02T21:27:19.758788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:27:19.758788Z digest=sha256:583da5dff280dbbf528a9e4408bec58948359db3633e21d3a4ecf721bb9b2bcd

Observation 9b4ec1fb-9fa2-4f04-98ed-6cf0d195cd7f · inbound

Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data cites this paper.

Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data A Reproducible Extraction of Training Images from Diffusion Models

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:11:27.265809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T12:22:43.354047Z digest=sha256:560fac3ab0fde7b26653b3aa27a39cc619a3fff30303f7adb44af6c48be9fe4c

Observation d01c1d8f-b3bb-46aa-8137-6ced477843b1 · inbound

Memorization In Stable Diffusion Is Unexpectedly Driven by CLIP Embeddings cites this paper.

Memorization In Stable Diffusion Is Unexpectedly Driven by CLIP Embeddings A Reproducible Extraction of Training Images from Diffusion Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:15:48.069144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T20:08:44.607763Z digest=sha256:b7dc7a6142de2013e77cf96b420ffcc9ab482d4ebb71b56c860f0410d15d6099

Observation 6df9595e-bad4-4d53-bb40-fac41f03fba3 · inbound

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations cites this paper.

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations A Reproducible Extraction of Training Images from Diffusion Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-22T06:36:10.233608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T06:35:15.725777Z digest=sha256:25b70552288cd7c2d1f5e8549f22ddd0e8f42f72cd84c94f0fbb948a44d9c0e8

Observation fb1aa545-6815-471b-aa32-761f4127d051 · inbound

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations cites this paper.

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations A Reproducible Extraction of Training Images from Diffusion Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-25T06:10:23.687866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T06:09:15.842739Z digest=sha256:1f9ab7e0600defbee4a7caa8a4ee16ad021742cb251c3c341d063be4461e7060

Observation b459280e-6e53-4025-aef7-b802b2fe43c6 · inbound

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations cites this paper.

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations A Reproducible Extraction of Training Images from Diffusion Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-01T15:05:48.272702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T17:36:54.119142Z digest=sha256:29e8a3c06adf5145730fc3a2a0f9f716cb3c3c2b9d03e7df716975e710e77202

Observation 99e8dcbc-adac-42ef-b704-a7c80714ebb9 · inbound

Conf-Gen: Conformal Uncertainty Quantification for Generative Models cites this paper.

Conf-Gen: Conformal Uncertainty Quantification for Generative Models A Reproducible Extraction of Training Images from Diffusion Models

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:03:29.718941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-29T13:55:03.982082Z digest=sha256:6a5a088199a47c6752c827570f7d8b8e7d219ea3b0f5a7b1beb7a6cf2d6f3d2a