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Paper Citation Record · LEDGER

GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.02968.

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

pith.paper-citation-record.v1
2406.02968 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:25:15.105547Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:31:08.314379Z

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 008e850c-4040-40d6-8b7d-4ff3108adb42 · inbound

CoSurfGS:Collaborative 3D Surface Gaussian Splatting with Distributed Learning for Large Scene Reconstruction cites this paper.

CoSurfGS:Collaborative 3D Surface Gaussian Splatting with Distributed Learning for Large Scene Reconstruction GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T05:25:15.105547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:25:15.105547Z digest=sha256:ab49312109c1c217e4d433a96a740fe4988a92c321cf7cfc4276708b70373b1c

Observation 74915187-9c66-4ddf-a0cb-fa4e1a59dd6e · inbound

Disentangling 3D from Large Vision-Language Models for Controlled Portrait Generation cites this paper.

Disentangling 3D from Large Vision-Language Models for Controlled Portrait Generation GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:31:08.319241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T00:31:07.971098Z digest=sha256:7c500b71db12a83cd5620279bff4745648f3b5f7bcd1cadf02f0a75123d8c70d