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Paper Citation Record · LEDGER

On the Robustness of Segment Anything

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.16220.

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

pith.paper-citation-record.v1
2305.16220 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:26:30.619552Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T06:44:18.757244Z

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 6502297a-8304-4399-aded-07a352e4e027 · inbound

Promptable Anomaly Segmentation with SAM Through Self-Perception Tuning cites this paper.

Promptable Anomaly Segmentation with SAM Through Self-Perception Tuning On the Robustness of Segment Anything

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T12:26:30.619552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:26:30.619552Z digest=sha256:1c598b693ecf33244e0d03c9a3179974f715f58a605909ef7596092f81676a2f

Observation b78f2d46-0d51-47ef-9122-d9ed6bb4c198 · inbound

SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments cites this paper.

SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments On the Robustness of Segment Anything

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T10:48:44.970401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:48:44.970401Z digest=sha256:ff8d42a28ae5e07632abc45647102b5db2cac851e5fe6d26764d0e0a9d88f8ae

Observation d6dce785-1d33-4d3c-b422-cf4e06ad196b · inbound

Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation cites this paper.

Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation On the Robustness of Segment Anything

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T22:48:10.872394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:48:10.872394Z digest=sha256:487c00ba3c9a20f543499b4fff4c83d3b9cdb302e631b4d60fe2aa3af2fcdd7a

Observation 4b6c53b3-3d79-462e-a3de-763eef5fa2d2 · inbound

Segment Any-Quality Images with Generative Latent Space Enhancement cites this paper.

Segment Any-Quality Images with Generative Latent Space Enhancement On the Robustness of Segment Anything

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:47:15.717221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T23:45:38.970279Z digest=sha256:88bcf291444bfb1242770482e1a8c6d2a16993f0c3c3454d882a79ee69f9d06a

Observation d89cfa7c-e88b-415f-84f4-171aab44647d · inbound

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement cites this paper.

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement On the Robustness of Segment Anything

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T18:13:13.196181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T18:11:47.141366Z digest=sha256:e429cba3173bfc2ed9842d61d21b9187705678c1ec17e2a02cc9923c4deba5b6

Observation 5f3973c2-dcc8-4bbe-9fc6-473f0859cd0b · inbound

PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation cites this paper.

PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation On the Robustness of Segment Anything

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:44:18.758622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T06:42:32.719983Z digest=sha256:799238223f539bb6565e8d6ff68e690849f634c2ad7131a1f6e05e88f327c5b5