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Paper Citation Record · LEDGER

Better Call SAL: Towards Learning to Segment Anything in Lidar

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.13129.

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

pith.paper-citation-record.v1
2403.13129 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 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:48:59.836892Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0d3f6726-586c-4d9b-84c6-1d9a11da3c2c · inbound

GeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation cites this paper.

GeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation Better Call SAL: Towards Learning to Segment Anything in Lidar

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T18:48:59.836892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:48:59.836892Z digest=sha256:abd0270b29f16359ab235733776b70afd3c975d20d848aeeadea54aae6ffeb3e

Observation 815a2ae9-0066-4130-9d91-af98d9d92658 · inbound

ClickSeg3D: Few-Click Interactive Segmentation via Semantic Embeddings cites this paper.

ClickSeg3D: Few-Click Interactive Segmentation via Semantic Embeddings Better Call SAL: Towards Learning to Segment Anything in Lidar

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:51:13.714001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T01:50:06.044957Z digest=sha256:46fda2b22af0b12a235ce3b2a7430bd6b50c4509ce271969ff9388d673eca683

Observation 1dda1181-c8c8-4b4a-a9f8-c10c6b87a7e3 · inbound

ClickSeg3D: Few-Click Interactive Segmentation via Semantic Embeddings cites this paper.

ClickSeg3D: Few-Click Interactive Segmentation via Semantic Embeddings Better Call SAL: Towards Learning to Segment Anything in Lidar

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:59:11.120640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-20T22:59:04.578699Z digest=sha256:38bdffd9fc58b008bb65d864d9454274797097bbb174b7f074a66cf558c8e188