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Paper Citation Record · LEDGER

Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1705.08868.

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

pith.paper-citation-record.v1
1705.08868 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:01:40.214023Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T21:01:00.314446Z

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 0ff980dc-6cbb-4282-b1d3-c348d54286ea · inbound

Learning Correlated Astrophysical Foregrounds with Denoising Diffusion Probabilistic Models cites this paper.

Learning Correlated Astrophysical Foregrounds with Denoising Diffusion Probabilistic Models Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T05:01:40.214023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:01:40.214023Z digest=sha256:48cf2f73cbd5ae2a23b0a3c20f515fafeea5c96b497abfb19c632330e9b8373e

Observation 48cdb5b6-e11c-4582-839b-000ca1033bb4 · inbound

Improving Diversity in Language Models: When Temperature Fails, Change the Loss cites this paper.

Improving Diversity in Language Models: When Temperature Fails, Change the Loss Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models

Reference 841

Resolution
verified exact
local_arxiv, observed 2026-08-05T21:01:00.320266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T21:00:58.762864Z digest=sha256:ec9cca2ed021780fbf44f9d4741ab001673a52287c927928a58a5adb7db6725c