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Paper Citation Record · LEDGER

Instance Segmentation for Point Sets

As of 14 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2505.14583.

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

pith.paper-citation-record.v1
2505.14583 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:35:47.204392Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

9 of 9 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d0aa72a-aadd-4c96-a414-a37274f4e345 · outbound

This paper cites Zamir A., Jiang H., Brilakis I., Fischer M., Savarese S.

Instance Segmentation for Point Sets Zamir A., Jiang H., Brilakis I., Fischer M., Savarese S

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:47.169303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:47.169303Z digest=sha256:75cef517c1e66d754fed5452c2bf55a3ce80a973afa0ce48295f5ee008aa5f83

Observation f2d6f9f4-8fb1-4079-95ef-a74476787f1d · outbound

This paper cites A Review on Deep Learning Techniques Applied to Semantic Segmentation.

Instance Segmentation for Point Sets A Review on Deep Learning Techniques Applied to Semantic Segmentation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:47.174345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:47.174345Z digest=sha256:13d1eaf1b9ec4a8db28392845bb139996a5453494f8a3d8539c2a5ee86e033b4

Observation 8636fee0-33af-495f-b96b-2f9a9d8ab922 · outbound

This paper cites : The handbook of brain theory and neural networks.

Instance Segmentation for Point Sets : The handbook of brain theory and neural networks

Reference 3

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T15:35:47.364904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-07T15:35:47.179097Z digest=sha256:b68e24ada9255a9674065b44b03a2f498c6e96f3425f1e5b52d1a71b59916ee2

Observation 3989ed26-024b-4a9e-8fe0-bbb59d69cd02 · outbound

This paper cites MegaDepth: Learning Single-View Depth Prediction from Internet Photos.

Instance Segmentation for Point Sets MegaDepth: Learning Single-View Depth Prediction from Internet Photos

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:47.183209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:47.183209Z digest=sha256:9f35f434d26b66fa95825f33e74cb34517a3b0220eab06ae50ae38c2ff86b9f6

Observation c4fefa9e-f347-4c61-8e82-4d628f83ec38 · outbound

This paper cites PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation.

Instance Segmentation for Point Sets PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:47.187518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:47.187518Z digest=sha256:1533932fab11ef808cd71def3c06032c290b52f3f20487afebac796866a07a31

Observation 9bd476a1-d6c2-4cef-8438-cd3cd0e74391 · outbound

This paper cites R., Yi L., Su H., Guibas L.

Instance Segmentation for Point Sets R., Yi L., Su H., Guibas L

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:35:47.410368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-07T15:35:47.191650Z digest=sha256:c1bc5fc27fd16067ffaf92c096b8de79c09e3270f316c0153db800054d0a5714

Observation b030b189-0339-4f25-846a-be772f85701a · outbound

This paper cites SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation.

Instance Segmentation for Point Sets SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:35:47.255976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-07T15:35:47.196044Z digest=sha256:11b67c3c05fabe56a85dfc109ca44ffcfc0a66b5196d7f53c96cbe5961e4e458

Observation 74bacc61-ac91-4710-9c46-1b6e9445fba8 · outbound

This paper cites an unresolved cited work.

Instance Segmentation for Point Sets Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:35:47.398625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-07T15:35:47.200183Z digest=sha256:99669105a5970e8a066acdb7090a0eff649f3add5e058acbbb53d1b83fd6f2bc

Observation a0f30070-de46-473d-adb7-258fdcb793bc · outbound

This paper cites write newline.

Instance Segmentation for Point Sets write newline

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:47.204392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:47.204392Z digest=sha256:883f3b77ebd8fc38ee7afee60cce6edae28f8372cf66f46199166da2d3e80f72

Pith citing papers

No inbound Pith citation observations are available.