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Paper Citation Record · LEDGER

An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.14870.

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

pith.paper-citation-record.v1
2405.14870 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:32:35.365025Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:32:35.729523Z

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 b7411782-d9d2-4027-bcb2-11cc1ddda8c5 · inbound

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations cites this paper.

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models

Reference 73

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:32:35.734773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:32:35.365025Z digest=sha256:2aae02dfa2fe3359d4d0597dc956bf5c27f8a12c63e63d8f3e12caa8177557b1

Observation 4aa22563-814c-4390-8055-4560c537d120 · inbound

UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles cites this paper.

UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T20:54:12.714994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:54:12.714994Z digest=sha256:f456461de883d866bf5264c539e11472e3e5cc7316160c2f7bafc4d968b464ae