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Paper Citation Record · LEDGER

RENO: Real-Time Neural Compression for 3D LiDAR Point Clouds

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.12382.

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

pith.paper-citation-record.v1
2503.12382 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 2026-08-07T15:31:05.152228Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T00:38:29.681141Z

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 13787c37-fd42-46e4-84d8-a8f54feb1aa4 · inbound

A Novel Benchmark and Dataset for Efficient 3D Gaussian Splatting with Gaussian Point Cloud Compression cites this paper.

A Novel Benchmark and Dataset for Efficient 3D Gaussian Splatting with Gaussian Point Cloud Compression RENO: Real-Time Neural Compression for 3D LiDAR Point Clouds

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T15:31:05.152228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:31:05.152228Z digest=sha256:190399fcc69ec67dfc06b43e2cfb777884fab7d9f6e9280481204d9a84effdf7

Observation 6b05d4f5-f583-411d-9a2b-ece92560c8ef · inbound

Proteus: A Truncation-Robust Entropy Model for Progressive LiDAR Compression cites this paper.

Proteus: A Truncation-Robust Entropy Model for Progressive LiDAR Compression RENO: Real-Time Neural Compression for 3D LiDAR Point Clouds

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T00:38:29.782135Z

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=arxiv_source observed=2026-08-05T00:38:28.198343Z digest=sha256:ba61dd4cbbd64b33e917c337aeaa9be599d2617a1be28c95cf05499776d32248