Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2107.02908.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T04:33:45.010405Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T17:14:59.524859Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 517983a1-358b-451b-bdce-ded4989582d9 · inbound
Learning Broken Symmetries with Approximate Invariance Particle Convolution for High Energy Physics
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4cde55a-740f-44d7-84bd-1fd006ae2f29 · inbound
IAFormer: Interaction-Aware Transformer network for collider data analysis Particle Convolution for High Energy Physics
Reference 63
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.
Observation 4c7f9922-fde7-4285-8e88-bbadda448c54 · inbound
KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging Particle Convolution for High Energy Physics
Reference 7
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.
Observation d3bcc87e-fe05-4997-aeda-2cf9a2052335 · inbound
KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging Particle Convolution for High Energy Physics
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2cf05f50-a3fc-4e7b-8516-7e1e81f5a055 · inbound
Predict before you train: Scaling Laws for particle physics foundation models Particle Convolution for High Energy Physics
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.