Paper Citation Record · LEDGER

MolecularRNN: Generating realistic molecular graphs with optimized properties

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1905.13372.

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

pith.paper-citation-record.v1
1905.13372 v1

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 2026-08-04T06:34:03.388597+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T13:39:10.685304Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T12:01:00.386216Z

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 6f495a40-2fc3-4457-bc1d-c965ef1c3922 · inbound

Equivariant Efficient Joint Discrete and Continuous MeanFlow for Molecular Graph Generation cites this paper.

Equivariant Efficient Joint Discrete and Continuous MeanFlow for Molecular Graph Generation MolecularRNN: Generating realistic molecular graphs with optimized properties

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-04T23:40:32.546606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1e482a81-0c90-42ff-9ab0-9d837ebbbcbf · inbound

How Creative Are Large Language Models in Generating Molecules? cites this paper.

How Creative Are Large Language Models in Generating Molecules? MolecularRNN: Generating realistic molecular graphs with optimized properties

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-04T23:40:32.546606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d52efc02-7f9f-47f0-98f4-fa8eb2a23f8b · inbound

Fine-Grained Graph Generation through Latent Mixture Scheduling cites this paper.

Fine-Grained Graph Generation through Latent Mixture Scheduling MolecularRNN: Generating realistic molecular graphs with optimized properties

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-04T23:40:32.546606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9c00d5ed-1a0f-4d4a-b0ec-6a7b36183712 · inbound

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation cites this paper.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation MolecularRNN: Generating realistic molecular graphs with optimized properties

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T13:39:10.685304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.