Paper Citation Record · LEDGER

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning

As of 15 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 4 inbound Pith citation observations for arXiv:2505.19522.

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

pith.paper-citation-record.v1
2505.19522 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:51.271949Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:13:30.830018Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:02:32.271820Z

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy15
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1eab5663-16a2-4d8d-9e73-7ff2daaae2e2 · outbound

This paper cites Underwater image enhancement using generative adversarial networks: a survey.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Underwater image enhancement using generative adversarial networks: a survey

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:54.302096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a17c7bca-020e-4f70-babd-ab9e86f4db89 · outbound

This paper cites Well log data generation and imputation using sequence based generative adversarial networks.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Well log data generation and imputation using sequence based generative adversarial networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:54.020113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2817bb30-88c6-4751-8f5c-3ee4b99ac9c8 · outbound

This paper cites Diffusion mri gan synthesizing fibre orientation distribution data using generative adversarial networks.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Diffusion mri gan synthesizing fibre orientation distribution data using generative adversarial networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:53.827727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a494009f-c01e-401c-9c6a-fee3725d2cf2 · outbound

This paper cites A novel 3-step technique for 3d tumor reconstruction using generative adversarial networks and an attention-based long short-term memory.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning A novel 3-step technique for 3d tumor reconstruction using generative adversarial networks and an attention-based long short-term memory

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:53.675385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ff13418-41c1-4586-b7f1-c7157b059477 · outbound

This paper cites A semisupervised knowledge distillation model for lung nodule segmentation.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning A semisupervised knowledge distillation model for lung nodule segmentation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:53.494281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e1a58fca-d5ad-4db4-a38e-17b6f2d37c6d · outbound

This paper cites FTS: A Framework to Find a Faithful TimeSieve.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning FTS: A Framework to Find a Faithful TimeSieve

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:50.159417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3440dc2b-9ac6-45f0-b1af-cd85a8862fb9 · outbound

This paper cites Invariant spatiotemporal representation learning for cross-patient seizure classification.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Invariant spatiotemporal representation learning for cross-patient seizure classification

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:50.242431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 695695a9-bb3b-446d-9d64-4945cc00751e · outbound

This paper cites Causal recommendation via machine unlearning with a few unbiased data.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Causal recommendation via machine unlearning with a few unbiased data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:16:50.349529Z

Source-reported events for the cited work

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Observation c6d660f4-8cb5-4eb8-931e-b5b061e26232 · outbound

This paper cites Multimodal medical image fusion combining saliency perception and generative adversarial network.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Multimodal medical image fusion combining saliency perception and generative adversarial network

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:53.304303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a842410-53a9-470b-b4bb-78f397778b1c · outbound

This paper cites Tabular transformer generative adversarial network for heterogeneous distribution in healthcare.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Tabular transformer generative adversarial network for heterogeneous distribution in healthcare

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:53.151741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 007c7c99-608e-412b-b003-54d77e99ffcc · outbound

This paper cites Automatic segmentation and landmark detection of 3d cbct images using semi supervised learning for assisting orthognathic surgery planning.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Automatic segmentation and landmark detection of 3d cbct images using semi supervised learning for assisting orthognathic surgery planning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:52.987350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9f249d8-6e81-459c-a6b4-fa9627aba50a · outbound

This paper cites A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A strobe-compliant study.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A strobe-compliant study

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:52.841512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 31c39d69-e3a0-44a5-b9e9-f9a600c61bd9 · outbound

This paper cites A semisupervised learning approach for code smell detection.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning A semisupervised learning approach for code smell detection

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:52.651763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4c5c8799-5280-4bd6-b0e2-805e0f0ec8ec · outbound

This paper cites Safeguards-related event detection in surveillance video using semi-supervised learning approach.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Safeguards-related event detection in surveillance video using semi-supervised learning approach

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:52.348797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 41d861d2-2c64-49b6-b60f-400d765f60b7 · outbound

This paper cites Fldtmatch: Improving unbalanced data classification via deep semi-supervised learning with self-adaptive dynamic threshold.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Fldtmatch: Improving unbalanced data classification via deep semi-supervised learning with self-adaptive dynamic threshold

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:52.086613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9439531-43c6-41df-879d-3f78a0abcbe3 · outbound

This paper cites Semi-supervised learning techniques for detection of dead pine trees with uav imagery for pine wilt disease control.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Semi-supervised learning techniques for detection of dead pine trees with uav imagery for pine wilt disease control

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:51.796181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4b864c17-64cd-4a4f-b1b9-34083852733c · outbound

This paper cites Robust semi-supervised learning in open environments.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Robust semi-supervised learning in open environments

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:51.615276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 89093fd5-febd-4366-a138-5c062b352a72 · outbound

This paper cites Multi-parameter post-stack seismic inversion based on the cycle loop–semi- supervised learning.

Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning Multi-parameter post-stack seismic inversion based on the cycle loop–semi- supervised learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:16:51.477353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation bed74764-2d79-4bd3-924d-5fa6192b0cb0 · inbound

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems cites this paper.

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:13:30.830018Z

Source-reported events for the cited work

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Observation e18ca60d-5e6e-4e72-bcd7-3422ab27d184 · inbound

Research on Low-Latency Inference and Training Efficiency Optimization for Graph Neural Network and Large Language Model-Based Recommendation Systems cites this paper.

Research on Low-Latency Inference and Training Efficiency Optimization for Graph Neural Network and Large Language Model-Based Recommendation Systems Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:17.766281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40986fed-396b-494a-a6be-c05ac0b832b3 · inbound

Safe and Efficient Lane-Changing for Autonomous Vehicles: An Improved Double Quintic Polynomial Approach with Time-to-Collision Evaluation cites this paper.

Safe and Efficient Lane-Changing for Autonomous Vehicles: An Improved Double Quintic Polynomial Approach with Time-to-Collision Evaluation Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T13:30:23.718033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61789543-310a-4ed5-9873-6f818c1a89da · inbound

Scenario-based Decision-making Using Game Theory for Interactive Autonomous Driving: A Survey cites this paper.

Scenario-based Decision-making Using Game Theory for Interactive Autonomous Driving: A Survey Applications and Effect Evaluation of Generative Adversarial Networks in Semi-Supervised Learning

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:02:32.277625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.