Paper Citation Record · LEDGER

A Survey of Generative Techniques for Spatial-Temporal Data Mining

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2405.09592.

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

pith.paper-citation-record.v1
2405.09592 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:12:06.593183Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:01:33.985950Z

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 ada4c187-2b23-460a-837e-3a986db74aa3 · inbound

Prompt-based Unifying Inference Attack on Graph Neural Networks cites this paper.

Prompt-based Unifying Inference Attack on Graph Neural Networks A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T11:12:06.593183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3dd7f80-a3fa-473e-9c7a-604cc7438253 · inbound

Efficient Traffic Prediction Through Spatio-Temporal Distillation cites this paper.

Efficient Traffic Prediction Through Spatio-Temporal Distillation A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T20:27:02.972648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c744aa96-b8ee-4729-88fd-7d02253fdfd0 · inbound

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation cites this paper.

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 133

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:01:33.991094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f2cff8d-712e-4364-8b68-7ecc2b406e17 · inbound

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs cites this paper.

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:01:34.567225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cbe0314-d8ff-4d3b-af52-e8f69e1ca3f1 · inbound

FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction cites this paper.

FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T16:42:56.249154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4be7583-1d4d-4d60-aab2-9d52dbe18823 · inbound

UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration cites this paper.

UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:51:08.474326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b588ae1f-0100-4609-b740-2b30059b02f6 · inbound

Efficient Prompt Learning for Traffic Forecasting cites this paper.

Efficient Prompt Learning for Traffic Forecasting A Survey of Generative Techniques for Spatial-Temporal Data Mining

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:06:26.739852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.