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Paper Citation Record · LEDGER

LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.09256.

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

pith.paper-citation-record.v1
2309.09256 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:45:50.766475Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T01:45:51.302126Z

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 c373c3d5-ee79-4520-bc3d-346ff8ac6988 · inbound

OLiDM: Object-aware LiDAR Diffusion Models for Autonomous Driving cites this paper.

OLiDM: Object-aware LiDAR Diffusion Models for Autonomous Driving LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T05:45:50.766475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:45:50.766475Z digest=sha256:7c6f37fbd3638e28e148dd905603bda3a2082fc408300de591add0ec78f47206

Observation 3ec259fb-2e29-4627-a2b3-cf083953ea54 · inbound

LiDARDraft: Generating LiDAR Point Cloud from Versatile Inputs cites this paper.

LiDARDraft: Generating LiDAR Point Cloud from Versatile Inputs LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-03T14:33:55.690677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:33:55.690677Z digest=sha256:01667616a13eb39d9f9c31f957654e1f0a203ce0682ae6ff1d0e706ec6d13bc6

Observation 8ccd7718-ca88-4915-a3af-0f1372768cf5 · inbound

GEM: Generating LiDAR World Model via Deformable Mamba cites this paper.

GEM: Generating LiDAR World Model via Deformable Mamba LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:45:51.304428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-11T01:31:09.604703Z digest=sha256:63097668d9fb640745f1d3074c65c7068c916dea5445042d2bce17aea7b4be7e