Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.03139.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T16:34:28.696261Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T10:31:29.275837Z
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 01439957-5e73-40f7-abc0-56cac7cae143 · inbound
Inverse Design of Amorphous Materials with Targeted Properties cites this paper.
Inverse Design of Amorphous Materials with Targeted Properties Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks
Reference 80
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:34:28.696261Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d19d008c-95c8-4289-bbfd-2b9cb98ca9b7 · inbound
AMGenC: Generating Charge Balanced Amorphous Materials cites this paper.
AMGenC: Generating Charge Balanced Amorphous Materials Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:31:29.278887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1f71a704-5e66-4fac-ae52-662a93ad4cd1 · inbound
Augmented Equivariant Mesh Networks for Anatomical Segmentation cites this paper.
Augmented Equivariant Mesh Networks for Anatomical Segmentation Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T08:01:27.779036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.