Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.02748.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:39:52.435092Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation f106c278-45c3-421d-b0f9-6ba816947929 · inbound
Universal crystal material property prediction via multi-view geometric fusion in graph transformers cites this paper.
Universal crystal material property prediction via multi-view geometric fusion in graph transformers ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:39:52.435092Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39f9046f-7051-4dea-9b6d-c5fa079d31a1 · inbound
VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python cites this paper.
VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
Reference 286
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-11T16:18:08.062622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 27e4db33-803f-4d82-86e5-7ed633a803c1 · inbound
Dual-Level Atomic and Coordination Geometry Learning for Crystal Property Prediction Using Graph Neural Networks cites this paper.
Dual-Level Atomic and Coordination Geometry Learning for Crystal Property Prediction Using Graph Neural Networks ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T22:23:13.643808Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.