Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2011.07457.
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 2026-08-11T10:36:38.183479Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T08:26:02.003646Z
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 3c096f32-299c-4944-be3c-892512eaa65a · inbound
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights cites this paper.
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:36:38.183479Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6ab7f3a-25ce-41bd-b6d1-9064348091ea · inbound
Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory cites this paper.
Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T08:26:02.006120Z
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 b770179f-563d-4cb9-b130-789994b4ff73 · inbound
Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory cites this paper.
Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T16:35:12.911151Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.