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Paper Citation Record · LEDGER

Graph Reinforcement Learning for Exploring BSM Model Spaces

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.07203.

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

pith.paper-citation-record.v1
2407.07203 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:48:01.453834Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T10:27:14.513154Z

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 0b757a84-c495-40ca-a96b-8c67ca20219a · inbound

Generating particle physics Lagrangians with transformers cites this paper.

Generating particle physics Lagrangians with transformers Graph Reinforcement Learning for Exploring BSM Model Spaces

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T19:48:01.453834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:48:01.453834Z digest=sha256:d070e428a4e16993269c66b03e89a576f3d45bd6f4b46ef48a4f262960ffe95f

Observation 235b28b8-6361-4382-9fd0-8716724fbd86 · inbound

Towards AI-assisted Neutrino Flavor Theory Design cites this paper.

Towards AI-assisted Neutrino Flavor Theory Design Graph Reinforcement Learning for Exploring BSM Model Spaces

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-19T10:27:14.514566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T10:25:21.512411Z digest=sha256:734a691ae2efa2692c7e33e8d005316aab9fdc54c71050339d2fe5554bd22b0a

Observation da3c972d-0281-4530-b977-02e0c9ee0c56 · inbound

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency cites this paper.

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency Graph Reinforcement Learning for Exploring BSM Model Spaces

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-03T15:47:06.072967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:47:06.072967Z digest=sha256:e0fa05d8d341692624e651c2d03d1dd510c1d080e80f8ffc478cb2c5e36dbd05