Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.24169.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T10:19:25.265738Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T04:14:43.896724Z
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 4b9b2ae3-8c26-4652-b246-c1a115c07a1b · inbound
BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps cites this paper.
BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T10:19:25.265738Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a51d74ad-fe39-4094-ada4-760c98b64f18 · inbound
Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials cites this paper.
Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
Reference 102
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-09T04:14:43.902088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2a7b3ae6-5354-4aa8-8321-5c48531a5213 · inbound
Platonic Transformers: A Solid Choice For Equivariance cites this paper.
Platonic Transformers: A Solid Choice For Equivariance The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T12:27:30.773704Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.