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Paper Citation Record · LEDGER

Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.13450.

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

pith.paper-citation-record.v1
2303.13450 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T06:04:10.913043Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:18:54.647721Z

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 1ef16e62-7052-4ce4-9220-e401925f8880 · inbound

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization cites this paper.

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-09T06:04:10.913043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T06:04:10.913043Z digest=sha256:95465373c5087b458d7650071a0a60db4eac10351378eaf58dc2ea5379914ea4

Observation 0b8d5e4a-cd91-4190-b435-1a2cbef273cc · inbound

DreamScene: 3D Gaussian-based End-to-end Text-to-3D Scene Generation cites this paper.

DreamScene: 3D Gaussian-based End-to-end Text-to-3D Scene Generation Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:18:54.736185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:18:44.793941Z digest=sha256:106910b29a29787c538e056697643d08a415d8ce2efa5b59220e7e3418d96671