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Paper Citation Record · LEDGER

How to Understand Limitations of Generative Networks

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2305.16774.

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

pith.paper-citation-record.v1
2305.16774 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:39:56.591734Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:58:54.540677Z

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 06ccb7f5-8b56-4e1c-9406-52ee6f103559 · inbound

How to Unfold Top Decays cites this paper.

How to Unfold Top Decays How to Understand Limitations of Generative Networks

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T17:18:46.068281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:18:46.068281Z digest=sha256:35fb748ef93cf31968435d1a729453c070f84a2c3e006476fd0c1d4f224b9f1f

Observation 166cd129-387a-477e-86c4-823a8889815c · inbound

A universal vision transformer for fast calorimeter simulations cites this paper.

A universal vision transformer for fast calorimeter simulations How to Understand Limitations of Generative Networks

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-03T12:08:20.496010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:08:20.496010Z digest=sha256:71222f6aaf5a549810730e6d4202c317501f15c09deb8506a2354e2f67f4018a

Observation 2aa6c89f-bbf3-491e-b463-9ef82f5b92dd · inbound

Local Conformal Predictions for Calibrated Surrogates cites this paper.

Local Conformal Predictions for Calibrated Surrogates How to Understand Limitations of Generative Networks

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:58:54.542023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-03T19:29:34.070294Z digest=sha256:74d42d96e9a3c1d0c80a5508776ada0effcec1b0b52f48bd0bc3faed3db1f67f

Observation 60bada0c-9840-4419-9bb4-e458420990e4 · inbound

Learning Standard Model structure from LHC data with Riemannian flow matching cites this paper.

Learning Standard Model structure from LHC data with Riemannian flow matching How to Understand Limitations of Generative Networks

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-01T21:19:42.242158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T21:19:42.242158Z digest=sha256:32b1d664aeb829220ef8e92b04b8195d3669a78da5ffce2e34f6ffa0b591ba5e

Observation 1fbaa3ab-73ca-44e4-83f1-22f6473b0c5a · inbound

An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning cites this paper.

An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning How to Understand Limitations of Generative Networks

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-01T07:01:01.283995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:01:01.283995Z digest=sha256:3242ce964c2809694f2582dad76d04bd580fe26f0a0292057814c37c7cdc48d4

Observation 1fb64f63-1a7b-48f3-be12-65d7d3148e21 · inbound

Agentic Re-Casting using Agentic Re-Simulations cites this paper.

Agentic Re-Casting using Agentic Re-Simulations How to Understand Limitations of Generative Networks

Reference 145

Resolution
unresolved
no resolver link, observed 2026-08-01T04:29:11.830883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:29:11.830883Z digest=sha256:2e4754e9a43eefdad162f4afea8785fc71cc3edb6a50ca1acbea16ad99f7a1ba

Observation b2bb7065-c134-411d-8cc0-13237a4637bf · inbound

Neural Control Variates at LO and NLO cites this paper.

Neural Control Variates at LO and NLO How to Understand Limitations of Generative Networks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-07-30T18:12:21.642659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T18:12:21.642659Z digest=sha256:68bb92efa1ea9708f6ee0793f802ba5623a94b7b5e2ef86e894c99a755035bcc

Observation 1dabea1b-64c4-4906-9587-1fd43658c02b · inbound

Generative Amplification with Surrogate Monte Carlo cites this paper.

Generative Amplification with Surrogate Monte Carlo How to Understand Limitations of Generative Networks

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T14:39:56.591734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:39:56.591734Z digest=sha256:14cf35026794efa8b0116cf71c263db58534c063e5686cce13c97a99dc74ab25