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Paper Citation Record · LEDGER

A Generative Model for Molecular Distance Geometry

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1909.11459.

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

pith.paper-citation-record.v1
1909.11459 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:50:58.685402Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:20:28.538573Z

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 e88da4de-2328-4bd0-9991-7213f4d93944 · inbound

Graph Neural Networks in Modern AI-aided Drug Discovery cites this paper.

Graph Neural Networks in Modern AI-aided Drug Discovery A Generative Model for Molecular Distance Geometry

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T05:50:58.685402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:50:58.685402Z digest=sha256:f270b83a93afd7a64ae554088e1bbe25485733624ee92ac9f7d97ff20ab85a30

Observation 539d9617-a928-435d-b7f7-bb3099e4836d · inbound

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow cites this paper.

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow A Generative Model for Molecular Distance Geometry

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T17:56:04.959744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:56:04.959744Z digest=sha256:c236cce67bb84265abe8603f1040ccacb2ca3fe12d5b591da29b99300e8fa9ca

Observation 5603f95e-292a-4878-8aa7-821981d7c3ff · inbound

Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery cites this paper.

Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery A Generative Model for Molecular Distance Geometry

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:20:28.541495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T07:19:33.319408Z digest=sha256:31e0995b94804903a80d230eae43a51cd6c7ddc22003f233678241a0277580da

Observation e20e6161-4e68-4e94-8686-4a435c43fb7b · inbound

Expanding Flow Maps cites this paper.

Expanding Flow Maps A Generative Model for Molecular Distance Geometry

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-01T07:05:50.028775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:05:50.028775Z digest=sha256:c7309d687985ebe58fa2830600047ead038bee4241ef14b678e597a335039955