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Paper Citation Record · LEDGER

A Survey on Responsible Generative AI: What to Generate and What Not

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.05783.

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

pith.paper-citation-record.v1
2404.05783 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:48:29.459417Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:49:52.908736Z

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 d23795c1-04fa-4676-a70e-983ba50a9ccf · inbound

Global Challenge for Safe and Secure LLMs Track 1 cites this paper.

Global Challenge for Safe and Secure LLMs Track 1 A Survey on Responsible Generative AI: What to Generate and What Not

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:29.459417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:29.459417Z digest=sha256:34146dd59c0de6b4e892fd78bd6b02a2259cfb1a646a6738e50f8403de195d25

Observation 2cf2c84c-a42e-4f52-90cb-243bb14817f2 · inbound

UVCG: Leveraging Temporal Consistency for Universal Video Protection cites this paper.

UVCG: Leveraging Temporal Consistency for Universal Video Protection A Survey on Responsible Generative AI: What to Generate and What Not

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T13:30:24.299778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:30:24.299778Z digest=sha256:23a7c549ca36dd50da4b09c7bc1bb6df33aeff8633bb576d11369dce63575c62

Observation f7930752-df99-4fad-b256-ba8d862dca48 · inbound

Not Just Text: Uncovering Vision Modality Typographic Threats in Image Generation Models cites this paper.

Not Just Text: Uncovering Vision Modality Typographic Threats in Image Generation Models A Survey on Responsible Generative AI: What to Generate and What Not

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T20:41:16.069137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:41:16.069137Z digest=sha256:8d2483092820e528907cb5a1920e215fccfcae52de64c8a52af43d92fae831ff

Observation 3fe65785-adac-49ed-88af-d17da1d4242d · inbound

Comparative Insights on Adversarial Machine Learning from Industry and Academia: A User-Study Approach cites this paper.

Comparative Insights on Adversarial Machine Learning from Industry and Academia: A User-Study Approach A Survey on Responsible Generative AI: What to Generate and What Not

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:20:43.964624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T07:17:47.532984Z digest=sha256:f839561dca65abd06f7aa0cbe352c1627fb5412533a2f574d1d1e1fc3e92658a

Observation 8cda13a0-80cd-4abe-9d4e-c8c797347d17 · inbound

Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks cites this paper.

Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks A Survey on Responsible Generative AI: What to Generate and What Not

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:49:52.910698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-26T05:51:01.446139Z digest=sha256:5e4e2bc291e0c7ca8c4cfcc5ccb6280b28f7ae6201653968b317693d5dca7e7c