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Paper Citation Record · LEDGER

Learning to Generate 3D Shapes with Generative Cellular Automata

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2103.04130.

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

pith.paper-citation-record.v1
2103.04130 v1

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:53:58.766694Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T12:43:38.166680Z

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 ad41b189-bc99-47ff-9726-673509873f12 · inbound

Mixtures of Neural Cellular Automata: A Stochastic Framework for Growth Modelling and Self-Organization cites this paper.

Mixtures of Neural Cellular Automata: A Stochastic Framework for Growth Modelling and Self-Organization Learning to Generate 3D Shapes with Generative Cellular Automata

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T22:53:58.766694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:53:58.766694Z digest=sha256:7283e79fb3f78e6668f38e1046b1a0d6d1c0c92ca49f6ae6aff6acff99923c2f

Observation 069bfdf2-f9cf-441e-a031-c30f9c90bd0d · inbound

A Continuous-Time Consistency Model for 3D Point Cloud Generation cites this paper.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Learning to Generate 3D Shapes with Generative Cellular Automata

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-05T12:43:38.218300Z

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=2026-08-05T12:43:37.678002Z digest=sha256:267ac5d93214f41a70a8150b6f658e6c5e44d8bc6c9c55c0c37ce1d2b11cd4b2