Paper Citation Record · LEDGER

Semi-supervised semantic segmentation needs strong, varied perturbations

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1906.01916.

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

pith.paper-citation-record.v1
1906.01916 v5

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 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:28:46.333913Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:46:45.970014Z

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 261624f5-74fe-4978-85b6-20caa6c12b99 · inbound

P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation cites this paper.

P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:46.333913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 540b4a2f-7080-4796-a29b-9249f552cfea · inbound

Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation cites this paper.

Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T12:51:34.017839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4e89808-011f-40b9-8291-7049228f3144 · inbound

Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness cites this paper.

Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:18:51.071285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93f41c37-0481-4138-bb58-6b9fa34100f9 · inbound

FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation cites this paper.

FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:27.455028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9c316d0-184f-4347-b1d5-23725bb5e3c1 · inbound

Augment to Segment: Tackling Pixel-Level Imbalance in Wheat Disease and Pest Segmentation cites this paper.

Augment to Segment: Tackling Pixel-Level Imbalance in Wheat Disease and Pest Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T18:27:00.983374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a418bf5-f866-4e6a-a8d6-bbbf0d2c8ee9 · inbound

Implicit Fuzzification via Bounded Noise Injection for Robust Medical Image Segmentation cites this paper.

Implicit Fuzzification via Bounded Noise Injection for Robust Medical Image Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:46:45.971537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.