Paper Citation Record · LEDGER

DPA-2: a large atomic model as a multi-task learner

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2312.15492.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2312.15492 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T11:08:03.688246Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T20:18:56.332102Z

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 dc4a84e0-10f1-4621-9a2f-985350b10f1f · inbound

MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures cites this paper.

MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures DPA-2: a large atomic model as a multi-task learner

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:13:39.630114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 56904230-7283-4ea0-8632-57896cfc8a4d · inbound

Siamese Foundation Models for Crystal Structure Prediction cites this paper.

Siamese Foundation Models for Crystal Structure Prediction DPA-2: a large atomic model as a multi-task learner

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-05-23T00:15:15.032003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 128f96f3-57ea-4780-9f2d-7f0493d8f008 · inbound

GraphVec: Cross-Domain Graph Vectorization for Graph-Level Representation Learning cites this paper.

GraphVec: Cross-Domain Graph Vectorization for Graph-Level Representation Learning DPA-2: a large atomic model as a multi-task learner

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T07:27:31.635500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 294cce46-152a-4dae-9c19-c02acada7073 · inbound

ASTEROID: A Spatiotemporal Information Transformer for Forecasting Multi-Step Time Series of Molecular Dynamics cites this paper.

ASTEROID: A Spatiotemporal Information Transformer for Forecasting Multi-Step Time Series of Molecular Dynamics DPA-2: a large atomic model as a multi-task learner

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:18:56.334705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6cbe7f45-38d6-42ed-9ad1-84688456f377 · inbound

Toward Exascale AI for Science: A Scalable AI Skill for Autonomous Microkinetics Discovery cites this paper.

Toward Exascale AI for Science: A Scalable AI Skill for Autonomous Microkinetics Discovery DPA-2: a large atomic model as a multi-task learner

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-12T11:08:03.688246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68c1f5a6-5d11-4497-8a8e-bd6fc8f0bf37 · inbound

dpti: An Automated Thermodynamic Integration Workflow for Phase Diagram Calculations with Machine Learning Interatomic Potentials cites this paper.

dpti: An Automated Thermodynamic Integration Workflow for Phase Diagram Calculations with Machine Learning Interatomic Potentials DPA-2: a large atomic model as a multi-task learner

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-11T10:05:33.200630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.