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Paper Citation Record · LEDGER

TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.13802.

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

pith.paper-citation-record.v1
2408.13802 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 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:57:32.112182Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T19:22:50.737531Z

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 1ebb0e38-5623-49d7-97d8-e7584dece332 · inbound

DenoiseCP-Net: Efficient Collective Perception in Adverse Weather via Joint LiDAR-Based 3D Object Detection and Denoising cites this paper.

DenoiseCP-Net: Efficient Collective Perception in Adverse Weather via Joint LiDAR-Based 3D Object Detection and Denoising TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T18:57:32.112182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:57:32.112182Z digest=sha256:d0c3931bd101704cd65ce10b3203b721593932e75ec5e561d67be3b5367beed6

Observation 2c986b3e-6c20-4542-9a46-0df83cda5847 · inbound

Deep Learning For Point Cloud Denoising: A Survey cites this paper.

Deep Learning For Point Cloud Denoising: A Survey TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-05T19:44:35.931754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:44:35.931754Z digest=sha256:e0a1d28c26eb31306b0e6c973ee3762d8035ec7dce389d8398b7a951772f9265

Observation 85dbac24-db4a-4f1a-bfcb-d21e62601755 · inbound

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation cites this paper.

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:22:50.740812Z

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=2026-05-14T19:20:15.333859Z digest=sha256:e054bd19e7f4d65e6e28023f51d877681b22087bf829bd4331d2869a9f5f6840