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Paper Citation Record · LEDGER

Learning Trivializing Flows

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.08408.

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

pith.paper-citation-record.v1
2302.08408 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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T03:21:13.881357Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T03:22:21.191018Z

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 72ba89bd-0364-45a2-b9d2-ae8d7751b68d · inbound

Scaling flow-based approaches for topology sampling in $\mathrm{SU}(3)$ gauge theory cites this paper.

Scaling flow-based approaches for topology sampling in $\mathrm{SU}(3)$ gauge theory Learning Trivializing Flows

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:22:21.193886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-18T03:21:13.881357Z digest=sha256:9629e2585a436133150df26560673b1a373ed5a91dd2412a43521c48a66f4cdc

Observation 346ad039-f4a9-455a-bc8c-99b87e8331d6 · inbound

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition cites this paper.

Testing machine-learned distributions against Monte Carlo data for the QCD chiral phase transition Learning Trivializing Flows

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:10:58.611630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T01:54:10.924145Z digest=sha256:dacd135a1bf3643aa4d37e34d80f1a6f33285b53357cdec6acc67f54b45b9075