Paper Citation Record · LEDGER

LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.15393.

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

pith.paper-citation-record.v1
2305.15393 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:56:08.332445Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:36:55.562989Z

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 318c84bd-5cd2-4061-8061-30d38328e71c · inbound

Harlequin: Color-driven Generation of Synthetic Data for Referring Expression Comprehension cites this paper.

Harlequin: Color-driven Generation of Synthetic Data for Referring Expression Comprehension LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T14:56:08.332445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32ed574c-a15e-4127-b44e-fb49d7ed90a8 · inbound

SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation cites this paper.

SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T20:25:14.516822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da1aa099-20a3-46e0-a396-41eb294e5e9e · inbound

GeoProg3D: Compositional Visual Reasoning for City-Scale 3D Language Fields cites this paper.

GeoProg3D: Compositional Visual Reasoning for City-Scale 3D Language Fields LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T21:49:43.132312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dd7edcc-20d2-41b8-ab01-99bbde2eca25 · inbound

Embodied Spatial Intelligence: from Implicit Scene Modeling to Spatial Reasoning cites this paper.

Embodied Spatial Intelligence: from Implicit Scene Modeling to Spatial Reasoning LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Reference 266

Resolution: unresolved; no resolver link, observed 2026-08-05T13:38:20.875111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dda0a291-74e0-4055-87af-39cdf28ea324 · inbound

Aggregating LLM-Based Weak Verifiers for Spatial Layout Generation cites this paper.

Aggregating LLM-Based Weak Verifiers for Spatial Layout Generation LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:55.564288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 08b4b17e-d836-40a1-b6ff-038dadcdbdd3 · inbound

Think, Plan, Paint: Layout-Aware Reasoning for Controllable Image Generation in Unified Models cites this paper.

Think, Plan, Paint: Layout-Aware Reasoning for Controllable Image Generation in Unified Models LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T21:07:57.741701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.