Paper Citation Record · LEDGER

SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2104.14812.

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

pith.paper-citation-record.v1
2104.14812 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:58:30.587110Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:19:50.234281Z

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 cbd3ace2-a60c-4445-b4bb-83dca9ffa77c · inbound

Benchmarking Vision Foundation Models for Input Monitoring in Autonomous Driving cites this paper.

Benchmarking Vision Foundation Models for Input Monitoring in Autonomous Driving SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:17:35.616785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a94f2a10-2bce-4e1f-9c46-24966d57427f · inbound

MoViAD: A Modular Library for Visual Anomaly Detection cites this paper.

MoViAD: A Modular Library for Visual Anomaly Detection SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T16:58:30.587110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e6b9ace-c3c4-4ffa-ad65-fc2ebde55db3 · inbound

An aerial color image anomaly dataset for search missions in complex forested terrain cites this paper.

An aerial color image anomaly dataset for search missions in complex forested terrain SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T15:35:19.426084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba3ca0c2-77c5-44af-94f4-4691964bf1a0 · inbound

Uncertainty-Aware Likelihood Ratio Estimation for Pixel-Wise Out-of-Distribution Detection cites this paper.

Uncertainty-Aware Likelihood Ratio Estimation for Pixel-Wise Out-of-Distribution Detection SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T10:09:53.329384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32b6d210-282b-4e3b-bf8c-7aa6d0bf7806 · inbound

From Pixel to Mask: A Survey of Out-of-Distribution Segmentation cites this paper.

From Pixel to Mask: A Survey of Out-of-Distribution Segmentation SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T20:35:01.728444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa88a9b3-9004-49d1-b505-d79a1b827a46 · inbound

Real-World On-Vehicle Evaluation of Embedding-Based Anomaly Detection cites this paper.

Real-World On-Vehicle Evaluation of Embedding-Based Anomaly Detection SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:23:03.593189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f0df15e6-111e-4c04-97ab-ef453ec3a8b8 · inbound

The inattentional gap in task conditioned AI models that omit otherwise reportable safety critical signals cites this paper.

The inattentional gap in task conditioned AI models that omit otherwise reportable safety critical signals SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:19:50.235746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ffc76d52-566c-4588-8c5a-5a1ecbb2ae4f · inbound

The inattentional gap in task conditioned AI models that omit otherwise reportable safety critical signals cites this paper.

The inattentional gap in task conditioned AI models that omit otherwise reportable safety critical signals SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-12T11:58:52.700648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f4f103c-327f-48ea-8803-627d99ad1667 · inbound

The inattentional gap in task conditioned AI models that omit otherwise reportable safety critical signals cites this paper.

The inattentional gap in task conditioned AI models that omit otherwise reportable safety critical signals SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T04:42:46.286141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c688c23-31ab-477d-9cec-a4ea9011dc5a · inbound

Road-Aware Anomaly Segmentation with Query-Guided Polygons and CLIP in Autonomous Driving cites this paper.

Road-Aware Anomaly Segmentation with Query-Guided Polygons and CLIP in Autonomous Driving SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-11T20:13:45.453581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33fc0573-53b6-44cd-a2c8-f9a9d57d92a2 · inbound

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles cites this paper.

Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T05:56:23.337036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac3f34be-c1d4-4667-a3c3-1d3dff3e2fcf · inbound

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation cites this paper.

ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation

Reference 174

Resolution: unresolved; no resolver link, observed 2026-08-06T00:10:40.031833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.