Paper Citation Record · LEDGER

Learning Symbolic Physics with Graph Networks

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1909.05862.

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

pith.paper-citation-record.v1
1909.05862 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:32:13.600906Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T05:04:37.156892Z

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 5f81ed84-abae-4eb7-b757-1d874a3d0833 · inbound

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges cites this paper.

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning Symbolic Physics with Graph Networks

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:39:29.586442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 594bf6ae-6bae-45c2-b50b-a1c358e85f69 · inbound

Governing Equation Discovery from Data Based on Differential Invariants cites this paper.

Governing Equation Discovery from Data Based on Differential Invariants Learning Symbolic Physics with Graph Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T14:32:13.600906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed4ae075-dcb0-440e-bbcf-0df5f3e92cf7 · inbound

Positional Encoding meets Persistent Homology on Graphs cites this paper.

Positional Encoding meets Persistent Homology on Graphs Learning Symbolic Physics with Graph Networks

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T10:29:42.512499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb9f607e-d4b6-44bb-ad32-d7015f4571fd · inbound

Data-driven discovery of dynamical models in biology cites this paper.

Data-driven discovery of dynamical models in biology Learning Symbolic Physics with Graph Networks

Reference 119

Resolution: unresolved; no resolver link, observed 2026-08-04T23:15:50.553042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 866dc772-f529-43f0-ac85-411a289ee324 · inbound

When is a System Discoverable from Data? Discovery Requires Chaos cites this paper.

When is a System Discoverable from Data? Discovery Requires Chaos Learning Symbolic Physics with Graph Networks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T22:50:30.741913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92751630-8c10-4352-bf09-aab99d4ef497 · inbound

Interpretable Relational Inference with LLM-Guided Symbolic Dynamics Modeling cites this paper.

Interpretable Relational Inference with LLM-Guided Symbolic Dynamics Modeling Learning Symbolic Physics with Graph Networks

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T09:21:01.676949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1126fcac-576a-4493-8f9d-706d925e1fa1 · inbound

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits cites this paper.

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits Learning Symbolic Physics with Graph Networks

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:04:37.159847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.