Paper Citation Record · LEDGER

Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.08114.

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

pith.paper-citation-record.v1
2410.08114 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:47:18.559441Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:21:01.371975Z

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 1af8d278-5850-4cca-9a4e-fcf470efdd63 · inbound

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter cites this paper.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:18.559441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bd60bd8-d140-474a-98c2-943368356287 · inbound

HydraMamba: Multi-Head State Space Model for Global Point Cloud Learning cites this paper.

HydraMamba: Multi-Head State Space Model for Global Point Cloud Learning Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T14:04:42.324083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13a0caf9-f6bd-4859-a703-790dd036af71 · inbound

LIDARLearn: A Unified Deep Learning Library for 3D Point Cloud Classification, Segmentation, and Self-Supervised Representation Learning cites this paper.

LIDARLearn: A Unified Deep Learning Library for 3D Point Cloud Classification, Segmentation, and Self-Supervised Representation Learning Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:16:08.629192Z

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.

Observation 1790ac4b-a4fc-4050-a3c5-9c0a2baaedc5 · 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 Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:21:01.375300Z

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.