Paper Citation Record · LEDGER

Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2210.05274.

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

pith.paper-citation-record.v1
2210.05274 v1

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 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:05:01.373513Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:26:24.936149Z

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 c4fee63d-fd2d-4e48-8797-ec711e94974a · inbound

From Graph Diffusion to Graph Classification cites this paper.

From Graph Diffusion to Graph Classification Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T12:25:47.796896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a406f00c-9c38-43a2-a726-77649f77fb0b · inbound

Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation cites this paper.

Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T11:43:30.359927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8279923b-8f9b-418d-ab77-6187665bd48d · inbound

GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation cites this paper.

GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:35:36.787890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f86ec94-523a-4f84-96e5-408949f6531a · inbound

Multi-domain Distribution Learning for De Novo Drug Design cites this paper.

Multi-domain Distribution Learning for De Novo Drug Design Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T17:05:01.373513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8180df08-c738-4fba-a34a-a607c0f6e0d4 · inbound

Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling cites this paper.

Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:26:24.938405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 27d0dcae-08c0-43d2-acd5-231ddb070ae2 · 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 Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T22:02:31.560244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.