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Paper Citation Record · LEDGER

Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditions

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.16698.

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

pith.paper-citation-record.v1
2407.16698 v1

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:46:34.800977Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T10:46:34.937953Z

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 ef8aa0f3-485c-4527-b2ee-311af8a60cc5 · inbound

Stable-Sim2Real: Exploring Simulation of Real-Captured 3D Data with Two-Stage Depth Diffusion cites this paper.

Stable-Sim2Real: Exploring Simulation of Real-Captured 3D Data with Two-Stage Depth Diffusion Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditions

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:46:34.945122Z

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=2026-08-06T10:46:34.800977Z digest=sha256:a33c56449c419108091ba6edffbbd63889e5c5951e7175e63fd1dfdb212350de

Observation d731a83d-f5a4-497c-9b8b-44b285a2b17d · inbound

Boosting Robustness for All-Weather Self-Supervised Depth Estimation in Autonomous Driving cites this paper.

Boosting Robustness for All-Weather Self-Supervised Depth Estimation in Autonomous Driving Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditions

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T07:15:39.707326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:15:39.707326Z digest=sha256:913dcbf8ecfff8752a2dfa8463e1726e24e7479836e64b2a6671226bd76dca09