Pith. sign in

Paper Citation Record · LEDGER

PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1910.08287.

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

pith.paper-citation-record.v1
1910.08287 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:42.294484Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T23:55:15.004339Z

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 152fb454-8b3f-49b2-affd-f9ec5c05e068 · inbound

nuScenes: A multimodal dataset for autonomous driving cites this paper.

nuScenes: A multimodal dataset for autonomous driving PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-17T13:10:47.675404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T13:10:47.611999Z digest=sha256:d37d65daaaf1c8aa8423ca3791d1c4bc0eb59d5a945509a58fbe039e7976fdad

Observation a8e4f16e-b270-47ff-b679-ecadd6d2b695 · inbound

TARS: Traffic-Aware Radar Scene Flow Estimation cites this paper.

TARS: Traffic-Aware Radar Scene Flow Estimation PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:55:15.007696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T23:54:44.218963Z digest=sha256:ce84b5f9812ccbb34632042089478837c4199c1c9a8ad2f9f71e8f4b1ec1a7c9

Observation a5ab02e5-56cf-4e31-b610-df67dab9afbc · inbound

GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control cites this paper.

GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T13:13:42.294484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:42.294484Z digest=sha256:56d4a92da6e9092eb2b2dbb382a07d49f048d49003af177b5075aeefaf170d87

Observation 1c6fe23e-f788-4b67-a7b5-09d2aab6950f · inbound

4DPC$^2$hat: Towards Dynamic Point Cloud Understanding with Failure-Aware Bootstrapping cites this paper.

4DPC$^2$hat: Towards Dynamic Point Cloud Understanding with Failure-Aware Bootstrapping PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T05:11:31.770856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:11:31.770856Z digest=sha256:79d282c51435a1135a5cfaaf70ea14c37b797b08b7d4d9f2b83c1a2c81414f65

Observation 6686a67f-f6e8-4f87-86d8-dc1393b14e80 · inbound

STS-Mixer: Spatio-Temporal-Spectral Mixer for 4D Point Cloud Video Understanding cites this paper.

STS-Mixer: Spatio-Temporal-Spectral Mixer for 4D Point Cloud Video Understanding PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:21:01.381744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:00:52.439594Z digest=sha256:33df3f4e2a1079ea50ba0169de31ff73fcf5a978838dee5a79825527d8cc06b9