Paper Citation Record · LEDGER

Semi-supervised semantic segmentation needs strong, varied perturbations

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 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 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:25:31.251382Z

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
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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 7a86293b-133f-4799-9e1c-f6acb51a8e87 · inbound

Adaptively Augmented Consistency Learning: A Semi-supervised Segmentation Framework for Remote Sensing cites this paper.

Adaptively Augmented Consistency Learning: A Semi-supervised Segmentation Framework for Remote Sensing Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T20:47:52.887608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0291689f-3687-45ee-8865-cdf9125ddab9 · inbound

Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits cites this paper.

Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-12T11:03:34.983982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4897fe7-04f1-4e99-9f02-aad0456c6fd1 · inbound

The Last Mile to Supervised Performance: Semi-Supervised Domain Adaptation for Semantic Segmentation cites this paper.

The Last Mile to Supervised Performance: Semi-Supervised Domain Adaptation for Semantic Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T11:02:11.020105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e15ab1b-ef7f-476a-9fb3-f9eb2d5da094 · inbound

A Semi-Supervised Approach with Error Reflection for Echocardiography Segmentation cites this paper.

A Semi-Supervised Approach with Error Reflection for Echocardiography Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T05:08:42.060825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b74ebd60-980c-48b9-86d7-3b91a3bbc463 · inbound

Adversarially Domain-adaptive Latent Diffusion for Unsupervised Semantic Segmentation cites this paper.

Adversarially Domain-adaptive Latent Diffusion for Unsupervised Semantic Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T10:20:55.722734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d7f2af7-e594-4fd9-8ea6-29bdde1b030a · inbound

What is the Added Value of UDA in the VFM Era? cites this paper.

What is the Added Value of UDA in the VFM Era? Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T10:25:31.251382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 167b6841-5a9a-463a-8a87-ca74653197e1 · inbound

Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation cites this paper.

Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation Semi-supervised semantic segmentation needs strong, varied perturbations

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T22:13:23.392762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-21T06:32:19.484+00:00.