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Paper Citation Record · LEDGER

AdapterShadow: Adapting Segment Anything Model for Shadow Detection

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.08891.

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

pith.paper-citation-record.v1
2311.08891 v1

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 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:46:41.361293Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T20:57:23.216042Z

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 bfb52543-761a-4542-8f79-e7db71f03806 · inbound

When SAM2 Meets Video Shadow and Mirror Detection cites this paper.

When SAM2 Meets Video Shadow and Mirror Detection AdapterShadow: Adapting Segment Anything Model for Shadow Detection

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T00:46:41.361293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:46:41.361293Z digest=sha256:4c31b4c7afb43573f103f123147e9306b06e8e7471ed029bd5b70bb3362ff186

Observation 2ae420ef-27a3-4006-99d2-3f3b07680e8f · inbound

Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselines cites this paper.

Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselines AdapterShadow: Adapting Segment Anything Model for Shadow Detection

Reference 61

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T20:47:23.258213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-27T20:07:49.478014Z digest=sha256:7363d719febc50f2e0afdfa65a77cea713752d1ae272650c4f8295cc3d626e75

Observation 2a01df7c-622e-4821-b8a1-26cd4184e816 · inbound

Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline cites this paper.

Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline AdapterShadow: Adapting Segment Anything Model for Shadow Detection

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-07-02T20:57:23.217429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-27T20:03:13.515338Z digest=sha256:bd0c0af8d8d0f30fa8f47e115e0f995788bca570176c081bc057041d12dcbab3