Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.17015.
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 2026-08-07T04:59:06.336251Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T07:49:39.231730Z
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 b6ca7b83-5a22-4af6-80ab-f997545c3259 · inbound
Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames cites this paper.
Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:59:06.336251Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b72e7ee4-94b3-4b88-99cf-154c99099d6d · inbound
Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction cites this paper.
Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:06:28.469729Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 874f3723-9e47-47c0-bff9-53032231ba41 · inbound
Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework cites this paper.
Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T05:52:52.838159Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19f02273-1f89-4114-9926-ad2412b4e709 · inbound
$G^0W^0$ implementation based on the pseudopotential and numerical-atomic-orbital basis-set framework: Algorithms and benchmarks cites this paper.
$G^0W^0$ implementation based on the pseudopotential and numerical-atomic-orbital basis-set framework: Algorithms and benchmarks DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:07:08.856390Z
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 f80b60fa-7259-4fb9-91a5-8f537b8a8085 · inbound
AI-accelerated metallized $\sigma$-bonding screening for superconductor discovery cites this paper.
AI-accelerated metallized $\sigma$-bonding screening for superconductor discovery DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T07:49:39.233290Z
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.