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Paper Citation Record · LEDGER

A-NICE-MC: Adversarial Training for MCMC

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1706.07561.

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

pith.paper-citation-record.v1
1706.07561 v3

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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:48:46.762570Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-24T14:44:36.940687Z

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 5d7578dd-2208-4b4c-a921-078649a71b3c · inbound

Denoising Diffusion Implicit Models cites this paper.

Denoising Diffusion Implicit Models A-NICE-MC: Adversarial Training for MCMC

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-05-24T14:44:36.943370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-24T14:41:23.935708Z digest=sha256:743028d997839dc03de6e30c49f32bd59bd59f4296ac8b038193f8225c6c46f4

Observation 5dea7806-91cc-4746-8da8-3f0567ff67de · inbound

Schr\"{o}dinger Generator for High-Dimensional Integration and Sampling on Quantum Many-Body States cites this paper.

Schr\"{o}dinger Generator for High-Dimensional Integration and Sampling on Quantum Many-Body States A-NICE-MC: Adversarial Training for MCMC

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T00:48:46.762570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:48:46.762570Z digest=sha256:5796cc5c7983eb929623ee588bc144759fbb05ef64fab9e2f03104d1e413a7ad