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Paper Citation Record · LEDGER

SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.01451.

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

pith.paper-citation-record.v1
2406.01451 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:32:26.344729Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:01:03.909513Z

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 3cdf8809-b751-495b-836d-9e1bf3913149 · inbound

3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation cites this paper.

3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:26.344729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:26.344729Z digest=sha256:151e0a90ebb3319173630fae58bae7d30367012627c9964d376e1c1ff9b7998e

Observation 16354f4e-b6f4-4254-8590-8b1e97122d62 · inbound

SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation cites this paper.

SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:01:03.962090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T17:01:03.210476Z digest=sha256:bf43ac9ac18f53f88167dea359dd64e893750a8e5f940bc965ea8e420ca1a9bb