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Paper Citation Record · LEDGER

Unfolding with Generative Adversarial Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1806.00433.

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

pith.paper-citation-record.v1
1806.00433 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:48:37.459269Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-02T14:27:03.803937Z

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 b8416da6-f66a-44c6-8954-309060b92da2 · inbound

Simulation-Prior Independent Neural Unfolding Procedure cites this paper.

Simulation-Prior Independent Neural Unfolding Procedure Unfolding with Generative Adversarial Networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:37.459269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:37.459269Z digest=sha256:1974ea945da5aff087beddf626546a0fd21d42a6e3e97fe77299da6fcb91531c

Observation 7b8fdc32-c640-4de9-bac5-559ab7e84503 · inbound

Toward an event-level analysis of hadron structure using differential programming cites this paper.

Toward an event-level analysis of hadron structure using differential programming Unfolding with Generative Adversarial Networks

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T15:29:53.340132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:29:53.340132Z digest=sha256:c9a40e6856a0937671e0830e0b6cb06bb1ce0781b33df42f41474c512d084852

Observation f760a1fc-1c3b-4677-943b-3e6d88a26f52 · inbound

Reweighting Adversarial Networks for Unbinned Unfolding cites this paper.

Reweighting Adversarial Networks for Unbinned Unfolding Unfolding with Generative Adversarial Networks

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-02T14:27:03.805148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T00:28:42.520230Z digest=sha256:427ddcdac0abe9dcb6ae3bed88f7c76bee4d5a815db6c0aeff231e31fa6d9030