Paper Citation Record · LEDGER

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 2 inbound Pith citation observations for arXiv:2505.14481.

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

pith.paper-citation-record.v1
2505.14481 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:39:52.223635Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T23:07:21.558834Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T13:35:46.206066Z

Reference resolution

22 of 22 outbound references displayed

verified exact0
verified fuzzy9
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation be7037fd-03a9-4e96-a565-47d030b8dd06 · outbound

This paper cites It serves as an important transportation hub in the image.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models It serves as an important transportation hub in the image

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:56.995161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6188dfd6-6ff3-46aa-9b6f-a8c08c79988c · outbound

This paper cites These lines directly connect Beijing New Airport with the central urban area and surrounding regions.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models These lines directly connect Beijing New Airport with the central urban area and surrounding regions

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:56.858364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6582c367-896e-44d7-8bba-2c1c15ac24f4 · outbound

This paper cites These stations enable efficient transfers between rail transit and surface transportation.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models These stations enable efficient transfers between rail transit and surface transportation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:56.671018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 521ace9c-f81b-4d5a-ad4d-fe19ab03fcbf · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:56.487407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7f7572b6-8867-43ab-9f03-7cf06d29f56d · outbound

This paper cites Beijing New Airport.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Beijing New Airport

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:56.282515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 49ecf93c-8e85-4501-b307-86f3aad9c75c · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:54.952907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a55ada0e-b46e-44ea-b68a-427c71ae4ade · outbound

This paper cites In summary, Jiangsu’s approach to urban-rural integration aims to achieve comprehensive and harmonious development through coordinated planning and multifaceted policy support.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models In summary, Jiangsu’s approach to urban-rural integration aims to achieve comprehensive and harmonious development through coordinated planning and multifaceted policy support

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:54.524960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d057eb44-30ab-4739-8571-730a1ecc7034 · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:56.056799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41719250-66f1-46f1-a73c-b5c1204aaf77 · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:55.859062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 415b08ca-f3e5-4141-bdfe-e364cd1b12bf · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:55.593167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e62884e1-60c1-4905-8396-32c43d6b9a5d · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:55.433232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dd6dd569-dea6-4bbf-9545-e7bb4b72801d · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:55.165879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d93d8b20-d5e5-49e3-9a51-f0fac8467d89 · outbound

This paper cites comprehensive planning.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models comprehensive planning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:54.217080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd284921-6399-4b37-a709-81a1c913c96a · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:53.937323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c95af709-c449-45a6-8ead-26889cd77dd4 · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:53.677583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a536703-92c9-46b1-8962-fb714fa66400 · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:53.384582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a4bf7693-1675-4752-9089-6329dfc4247d · outbound

This paper cites an unresolved cited work.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:39:53.177141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 826f3425-76a9-4ac9-a9ea-476c2beb7a7f · outbound

This paper cites construction detailed plan.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models construction detailed plan

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:52.947660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ff1be909-0ac6-4680-924a-5c58451f8a21 · outbound

This paper cites regulatory detailed plan.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models regulatory detailed plan

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:52.662460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1a9bbf1b-70da-4e4f-b498-174cabaacddd · outbound

This paper cites Final Score: 0/2 Figure 14: Image of Evaluation Example 2 23.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Final Score: 0/2 Figure 14: Image of Evaluation Example 2 23

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:39:52.411189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 52166a51-173b-4065-baed-1b8849038595 · outbound

This paper cites Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:39:50.323121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df0f1739-e7f8-4840-946f-ee63e150e49b · outbound

This paper cites DeepSeek-V3 Technical Report.

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models DeepSeek-V3 Technical Report

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T15:39:50.410786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 7ec6c0ff-d64f-4ed0-8820-991ec4e050fe · inbound

Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.

Earth Science Foundation Models: From Perception to Reasoning and Discovery PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models

Reference 235

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:08:03.242679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c0686716-a7a4-4a36-a63f-df99d72e9c9d · inbound

Earth Science Foundation Models: From Perception to Reasoning and Discovery cites this paper.

Earth Science Foundation Models: From Perception to Reasoning and Discovery PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models

Reference 235

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.208115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.