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Paper Citation Record · LEDGER

Generative Adversarial Networks as Variational Training of Energy Based Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1611.01799.

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

pith.paper-citation-record.v1
1611.01799 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:45:24.894951Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:45:24.933941Z

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 791957fe-c66b-4335-be96-4f2b0db02347 · inbound

Exploring bidirectional bounds for minimax-training of Energy-based models cites this paper.

Exploring bidirectional bounds for minimax-training of Energy-based models Generative Adversarial Networks as Variational Training of Energy Based Models

Reference 86

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:45:24.939791Z

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=2026-08-07T10:45:24.894951Z digest=sha256:8138d7f46c3b92b2386e71457b44f773655f6516ab273a3b8b8426d4a78306d7