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Paper Citation Record · LEDGER

Learning Symbolic Physics with Graph Networks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 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 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:29:42.512499Z

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T02:39:29.411021Z digest=sha256:f405edd6e3eacb35cf0f66f21760c2d20cee6c8967a7a66e9ded1fe421e16062

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.

source=pdf_text observed=2026-08-07T10:29:42.512499Z digest=sha256:a6f48d36a0dc5db0f02f40dac54d24e1899b3352be4811e73aaa04a192e0233b

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.

source=pdf_text observed=2026-08-04T23:15:50.553042Z digest=sha256:32fdf194e1ea81ffaa131359a84be175ffbd3c21b08244cf0c5f7cb7c20aecaa

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.

source=arxiv_source observed=2026-08-03T22:50:30.741913Z digest=sha256:3511dbba406e50ebb9d842af811ac33fcb1d4a93dded4e2f07f87d61d740f259

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T16:04:40.839607Z digest=sha256:f2808757117fa75840796fd396faad7cbe4673a2d5cfc9c7a123e25156f2c6de

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T05:03:33.071351Z digest=sha256:24cde903dbd0466cfbd0f235b8380de0215362ece0bcfd6988351d77687861e9