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Paper Citation Record · LEDGER

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2402.15332.

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

pith.paper-citation-record.v1
2402.15332 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:27:15.912616Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3bd5f20b-76e8-4c7f-9442-db506106759e · inbound

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad cites this paper.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T20:27:15.912616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:27:15.912616Z digest=sha256:79fd391d7e607d26d382175c0e39dd1f315b4e35de40bea0a183e9f2071be066

Observation d6d37f2f-fe0e-4412-8d49-fa3ceec62a2f · inbound

Can neural operators always be continuously discretized? cites this paper.

Can neural operators always be continuously discretized? Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-11T22:33:25.427496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:33:25.427496Z digest=sha256:7e450597a12580c0cad8f24dca1ad21e459e9fbc7696b26472a8ee1e6843acbf

Observation 340013d3-3251-4196-bb2f-0efb89804bf3 · inbound

Algebra Unveils Deep Learning -- An Invitation to Neuroalgebraic Geometry cites this paper.

Algebra Unveils Deep Learning -- An Invitation to Neuroalgebraic Geometry Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-09T22:04:26.519620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T22:04:26.519620Z digest=sha256:9c6a3ac6170af75a484a25673818a665220fdd92f0122d92eaa446aaf2f68769

Observation 2ca92064-bf33-43fd-aeac-4b714b7ff635 · inbound

Relational inductive biases on attention mechanisms cites this paper.

Relational inductive biases on attention mechanisms Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T20:00:02.992586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:00:02.992586Z digest=sha256:43408bfc6265b3f67ba92ea3feeb339eb1fc20cebe61bbb197c9dc0adea2bc13

Observation b53dfcb0-1e56-48e7-ac5d-6058afe229fe · inbound

Topos Theory for Generative AI and LLMs cites this paper.

Topos Theory for Generative AI and LLMs Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T04:20:09.651169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T04:20:09.651169Z digest=sha256:0577b5a629d460043c0cf8d801674f10fdd28bc241167c7868f78244a86290da

Observation 99274788-605d-4c87-baf2-04550d97abec · inbound

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation cites this paper.

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T08:45:19.215953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-15T08:42:20.931132Z digest=sha256:19ded36bc6761bdcac199b59a00ef65264360b83892762009b7b621c83565e55

Observation 5026ac83-5cd0-4eea-8312-14e37bfbe915 · inbound

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation cites this paper.

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-13T23:04:18.864523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T23:04:18.864523Z digest=sha256:608b4f7b3771b26c61a175c09405eada1889b18adb4b40558dbb226e23536e6b

Observation 7d5ccc97-fc61-4a95-84fb-082508f890f1 · inbound

Decidable By Construction: Design-Time Verification for Trustworthy AI cites this paper.

Decidable By Construction: Design-Time Verification for Trustworthy AI Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:48:25.074197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-15T00:43:45.198512Z digest=sha256:362dbf70be2e3979bede826151b4fdbd584b6674bc7606aa84e58e82ca4ac588

Observation cf400ec4-d452-4f54-bb0d-2d190ff891a4 · inbound

Presenting Neural Networks via Coherent Functors cites this paper.

Presenting Neural Networks via Coherent Functors Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:03:24.921528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T09:01:41.578635Z digest=sha256:a4ef939cf5b690b3515aba5d8cd4a9900392a7b8958f6913faca1bf4c464b762

Observation 6874d61a-db55-4871-a08e-96f379eb3601 · inbound

From Mechanistic to Compositional Interpretability cites this paper.

From Mechanistic to Compositional Interpretability Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:46:18.491894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-12T02:42:26.173782Z digest=sha256:84e9c8da4615f305a80290571952ea410bdab122c67308477387ab97ec7286ce

Observation 5e042b6d-e75c-47f4-afc3-278f4125ba41 · inbound

Scheme-invariant stratified factorization algebras for inclusive deep inelastic scattering cites this paper.

Scheme-invariant stratified factorization algebras for inclusive deep inelastic scattering Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-20T16:18:37.639346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T16:14:29.720457Z digest=sha256:5e846c0d2081ebdf8287cb2cc1670e1e29f4b00d4c7f697682df208a2cd97746

Observation 021a210f-9e35-4763-8688-db0e3dda9fd2 · inbound

Operadic consistency: a label-free signal for compositional reasoning failures in LLMs cites this paper.

Operadic consistency: a label-free signal for compositional reasoning failures in LLMs Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T15:18:33.047197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-27T06:37:20.362458Z digest=sha256:8e5bd069ee3fe8876a3a547c523c7d83356f30cef127ff3d9f018c2b2cd7c108