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Paper Citation Record · LEDGER

Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1801.01726.

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

pith.paper-citation-record.v1
1801.01726 v2

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:47:54.048491Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T23:30:59.573281Z

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 85284631-fcc9-4280-bf11-28393888d011 · inbound

Training Deep Learning Models via Synthetic Data: Application in Unmanned Aerial Vehicles cites this paper.

Training Deep Learning Models via Synthetic Data: Application in Unmanned Aerial Vehicles Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-14T12:47:54.048491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:47:54.048491Z digest=sha256:622365eb11fc3ad2cc7571670981cc8a9c4fe3ddd5e002da678be79fc2848be4

Observation be4e6d88-6eef-4f04-bccd-4ba72cbc2c1e · inbound

Generative Adversarial Networks Bridging Art and Machine Intelligence cites this paper.

Generative Adversarial Networks Bridging Art and Machine Intelligence Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption

Reference 199

Resolution
verified exact
local_arxiv, observed 2026-08-08T23:30:59.579029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-08T23:30:59.421685Z digest=sha256:ad819d2437285c274848fe99db86bdd87f6f85e4f6aac3dc92eeb9590be2a161