Paper Citation Record · LEDGER

Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1906.00957.

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

pith.paper-citation-record.v1
1906.00957 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:41:49.600906Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:36:25.604444Z

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 c3a37ae2-b3e3-4f5b-a7ae-3ed7c19a32d1 · inbound

LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation cites this paper.

LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T21:41:49.600906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5d172f1-0275-42cc-b160-51b1c2ccc7bc · inbound

Simulating the Hubbard Model with Equivariant Normalizing Flows cites this paper.

Simulating the Hubbard Model with Equivariant Normalizing Flows Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.244889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4696e5ee-c2ea-4ec1-9b6c-421e31a2bad0 · inbound

FLOWR.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction cites this paper.

FLOWR.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T12:42:50.057233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfbe1a0a-16c0-486d-baa5-64cad08e7426 · inbound

Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation cites this paper.

Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T11:28:54.541781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 925907fa-40fb-4c92-827e-319811df3639 · inbound

SLayerGen: a Crystal Generative Model for all Space and Layer Groups cites this paper.

SLayerGen: a Crystal Generative Model for all Space and Layer Groups Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:36:25.607057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fb899d44-6bf8-402b-8dab-ad39ad2949bd · inbound

Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement Learning cites this paper.

Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement Learning Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T22:02:30.951117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.