Pith. sign in

Paper Citation Record · LEDGER

Generative AI in Transportation Planning: A Survey

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2503.07158.

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

pith.paper-citation-record.v1
2503.07158 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:13:52.217137Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:06:19.566266Z

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 e112dbea-fdac-497c-9c04-636fe7905072 · inbound

LangCoop: Collaborative Driving with Language cites this paper.

LangCoop: Collaborative Driving with Language Generative AI in Transportation Planning: A Survey

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T12:13:52.217137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:13:52.217137Z digest=sha256:288620be6eb0236dc1432374b19bb2d2b0ebb9910217090935e03aaf3070eb60

Observation a39c1e20-4424-4847-a8f9-bd4d8269585b · inbound

Generative AI for Autonomous Driving: Frontiers and Opportunities cites this paper.

Generative AI for Autonomous Driving: Frontiers and Opportunities Generative AI in Transportation Planning: A Survey

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-15T21:49:12.890633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:49:12.890633Z digest=sha256:5c51b72d18525985638e26df10c5b4c04c40207b129f26e76f1093e9480e41b7

Observation d05e231e-8423-4167-9bc7-c929650e7d75 · inbound

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios cites this paper.

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios Generative AI in Transportation Planning: A Survey

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:21:35.744331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T13:18:30.486507Z digest=sha256:24833a507dcce6fad0f990b90d7896b92a933abd16bdae8c6266acd371944da1

Observation 4a938654-956d-4e42-8da6-4dfdfbf5248c · inbound

DeepShade: Enable Shade Simulation by Text-conditioned Image Generation cites this paper.

DeepShade: Enable Shade Simulation by Text-conditioned Image Generation Generative AI in Transportation Planning: A Survey

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T16:58:56.817922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:56.817922Z digest=sha256:dcd892d8b0fbb5441fd7e7ec6b7c53f69fe463dc77e09d1b6fc7937592216938

Observation f2909fc5-ef2d-4340-9c12-cb42305ca29b · inbound

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial Generative AI in Transportation Planning: A Survey

Reference 271

Resolution
unresolved
no resolver link, observed 2026-08-05T04:50:32.548019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:50:32.548019Z digest=sha256:1e3f83c4b879089d1bb42df4596e35ea0a37ddbf601e24ebc698ba4ee7e150ac

Observation 28da0ea0-c3d4-4176-b5c4-c58fea3f7f2c · inbound

A Two-Level Plackett-Luce Model for preference modeling in smart mobility platforms cites this paper.

A Two-Level Plackett-Luce Model for preference modeling in smart mobility platforms Generative AI in Transportation Planning: A Survey

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T22:01:11.902816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-08T03:36:34.050285Z digest=sha256:0537e2d26da250dcc0ac0ad13c494cc80c45a367d11186444b73a334bc4f7dd1

Observation 957f9aae-2c22-49d5-8a94-e940f9b59289 · inbound

Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries cites this paper.

Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries Generative AI in Transportation Planning: A Survey

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:04:45.647071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-22T09:04:24.857120Z digest=sha256:dccb483eb7c7cfe2f24d17a91b61a81812b4d699658cf4091e7c19620cbbd363

Observation 0398efc6-da0d-43a3-89ec-28b656fb5096 · inbound

MobEvolve: An Agentic Self-Evolving Heuristic System for Interpretable Human Mobility Generation cites this paper.

MobEvolve: An Agentic Self-Evolving Heuristic System for Interpretable Human Mobility Generation Generative AI in Transportation Planning: A Survey

Reference 89

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:06:19.568854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T14:47:16.208290Z digest=sha256:028ef1341d80c8d6de7e891167734384c771c8b704997d4d79ed6f47eb7defe3