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Paper Citation Record · LEDGER

LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2401.15865.

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

pith.paper-citation-record.v1
2401.15865 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:26:47.808278Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:26:48.662843Z

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 dfc9ba2d-05d7-4bc6-a44c-2e4c72e2189d · inbound

Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control cites this paper.

Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:26:48.766498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:26:47.808278Z digest=sha256:4d75cf6b313cd4a684d55a968880eba25b3a9aeb723e6dec1c04b250218294dc