Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2002.10964.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:12:17.070094Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T04:02:01.967361Z
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 13ac35a3-8d1e-4373-a470-58d33906cb12 · inbound
SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation cites this paper.
SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:12:17.070094Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad64c3e2-a551-427f-afe9-23e155f0542e · inbound
Hybrid Quantum-Classical Generative Adversarial Networks with Transfer Learning cites this paper.
Hybrid Quantum-Classical Generative Adversarial Networks with Transfer Learning Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T04:02:01.969252Z
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 49054d7e-acac-4f94-9c24-bc4a8eaca371 · inbound
Geometry Preserving Loss Functions Promote Improved Adaptation of Blackbox Generative Model cites this paper.
Geometry Preserving Loss Functions Promote Improved Adaptation of Blackbox Generative Model Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:11:19.408001Z
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.