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Paper Citation Record · LEDGER

Learning to Generate 3D Shapes with Generative Cellular Automata

As of 23 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 2026-08-23T06:30:58.430688+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:e88375b1c46f747cdd5b7173e83d28e4fa1bb9630d4e06d85d5f6db755fc6422

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-05T12:43:37.678002Z digest=sha256:72b5a556edee90d7a68152044f4efe42621a51bee49ef42c086278ef70515259