Paper Citation Record · LEDGER

Robustness of SAM: Segment Anything Under Corruptions and Beyond

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2306.07713.

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

pith.paper-citation-record.v1
2306.07713 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:51:47.941997Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T06:44:18.759917Z

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 45134c5f-af89-4756-8b22-0540167603d4 · inbound

Faster Segment Anything: Towards Lightweight SAM for Mobile Applications cites this paper.

Faster Segment Anything: Towards Lightweight SAM for Mobile Applications Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:41:43.476397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b883b2d-3a81-4c3e-88c9-1a976311474b · inbound

Benchmarking the Robustness of Optical Flow Estimation to Corruptions cites this paper.

Benchmarking the Robustness of Optical Flow Estimation to Corruptions Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T14:51:47.941997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff4281ab-5de5-4eb3-a88d-e74f4aa57246 · inbound

Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise cites this paper.

Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T10:13:16.354472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03f03a2b-b39f-45ae-876e-b29caf2a6278 · inbound

Towards Communication-Efficient Adversarial Federated Learning for Robust Edge Intelligence cites this paper.

Towards Communication-Efficient Adversarial Federated Learning for Robust Edge Intelligence Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T14:31:41.302251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e084ebd4-f5c9-4e57-88cc-dee88f69ea3f · inbound

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

Segment Any-Quality Images with Generative Latent Space Enhancement Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:47:15.723623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a21ccc90-9f19-4a22-8374-501bbde5de41 · inbound

A Survey on Foundation Models for Personalized Federated Intelligence cites this paper.

A Survey on Foundation Models for Personalized Federated Intelligence Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-22T15:34:57.835882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dc046888-fb2f-47ae-a583-7a46f328ccca · 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 Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T18:13:13.266601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 446e5a10-3c86-40e5-a3dd-8886c17f1695 · inbound

DeCoDrift: Stabilizing Decoder Coupling in Closed-Loop Foundation Segmentation cites this paper.

DeCoDrift: Stabilizing Decoder Coupling in Closed-Loop Foundation Segmentation Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T23:14:01.831968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 640d6fdd-7853-4c69-ba9e-db6ee2924c51 · 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 Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:44:18.761218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6bc7995-97e9-467e-95f0-9aa11b02d1ad · inbound

Universal Concept Disruption for SAM3 Image Segmentation cites this paper.

Universal Concept Disruption for SAM3 Image Segmentation Robustness of SAM: Segment Anything Under Corruptions and Beyond

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T19:56:39.314861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.