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Paper Citation Record · LEDGER

Toric geometry of ReLU neural networks

As of 23 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2509.05894.

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

pith.paper-citation-record.v1
2509.05894 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:28:38.100097Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T12:26:10.454497Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:16:24.156397Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy10
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1bfd4b2e-9215-4669-a416-de219d0f4cbf · outbound

This paper cites Understanding deep neural networks with rectified linear units.

Toric geometry of ReLU neural networks Understanding deep neural networks with rectified linear units

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.870327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:37.886680Z digest=sha256:f961e65cef004eb2b487ab0902cba69d56d651e963b31f2e90b46e7ea8836b9f

Observation 9fcdd3d3-874b-4cb2-9f43-65f657e574da · outbound

This paper cites Better neural network expressivity: subdividing the simplex.arXiv preprint arXiv:2505.14338, 2025.

Toric geometry of ReLU neural networks Better neural network expressivity: subdividing the simplex.arXiv preprint arXiv:2505.14338, 2025

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T16:28:37.892441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:28:37.892441Z digest=sha256:bc035751bc051063181120fec022f3016fe42009eff6e4e7df510dd8961e6730

Observation a4a915e8-2646-458c-b51f-2d9685ab9e2e · outbound

This paper cites American Mathematical Soc., 2011.

Toric geometry of ReLU neural networks American Mathematical Soc., 2011

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.852381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:37.897738Z digest=sha256:a239d9ae353678c2ca03e084992bfff335ef579cb25249befc9a457c3f61be44

Observation 21074f35-ef0c-4858-992f-5b18e79e0dd6 · outbound

This paper cites Activation degree thresholds and expressiveness of polynomial neural networks.

Toric geometry of ReLU neural networks Activation degree thresholds and expressiveness of polynomial neural networks

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.834344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:37.952085Z digest=sha256:d3d1a792bda8d9675cb727ac02921ee278e5b2e835f6246bb4b5418d35df2756

Observation b58a9ff4-6e5a-4ee7-aa94-8748506c7b83 · outbound

This paper cites On transversality of bent hyperplane ar- rangements and the topological expressiveness of relu neural networks.SIAM Journal on Applied Algebra and Geometry, 6(2):216–242, 2022.

Toric geometry of ReLU neural networks On transversality of bent hyperplane ar- rangements and the topological expressiveness of relu neural networks.SIAM Journal on Applied Algebra and Geometry, 6(2):216–242, 2022

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.748654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:37.993336Z digest=sha256:599a70c76d4e00d4350b127bf77993f02db01e6d229732e3df38d4712e6b54a1

Observation 05cafa5d-ac36-480f-bca8-4583eb90cfc1 · outbound

This paper cites Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes.

Toric geometry of ReLU neural networks Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T16:28:37.998632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:28:37.998632Z digest=sha256:d267844ec687d1e89a67bf9596864c3d96f6920e3af0ea3ac5829bdf674e8743

Observation 761eeaec-fc22-4edd-944d-6f4795491981 · outbound

This paper cites Towards lower bounds on the depth of relu neural networks.SIAM Journal on Discrete Math- ematics, 37(2):997–1029, 2023.

Toric geometry of ReLU neural networks Towards lower bounds on the depth of relu neural networks.SIAM Journal on Discrete Math- ematics, 37(2):997–1029, 2023

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.600213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:38.004909Z digest=sha256:3cc901d3867d104f2265c1381cbe79408db091992726dd791e28311763bfafbc

Observation 52696fe2-aded-4d69-a946-061239b246af · outbound

This paper cites Geometry of polynomial neural networks.Algebraic Statistics, 15(2):295–328, 2024.

Toric geometry of ReLU neural networks Geometry of polynomial neural networks.Algebraic Statistics, 15(2):295–328, 2024

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.581295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:38.010517Z digest=sha256:2db62231b76068f73ee392ac0610bb32dd396e49205c5b1d5f7085b1e6ec17d2

Observation fe624dc3-004d-49dd-9483-31f913681ed8 · outbound

This paper cites American Mathematical Society, 2021.

Toric geometry of ReLU neural networks American Mathematical Society, 2021

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.444376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:38.015959Z digest=sha256:eac0962aa23ddabdc057ee37106051e1afb0875cc75151b57ec7cd7134707587

Observation 9f3f6ce9-7954-4403-a64e-7e1addfc8b61 · outbound

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

Toric geometry of ReLU neural networks Algebra Unveils Deep Learning -- An Invitation to Neuroalgebraic Geometry

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T16:28:38.020965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:28:38.020965Z digest=sha256:b14c3c712c700abc2003f359d3ab251cf162a02a061ca149f07d869e1357917b

Observation efcafec0-8eca-4bcf-85b9-f97197e3a9ac · outbound

This paper cites Approximation theory of the mlp model in neural networks.Acta Nu- merica, 8:143–195, 1999.

Toric geometry of ReLU neural networks Approximation theory of the mlp model in neural networks.Acta Nu- merica, 8:143–195, 1999

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.343553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:38.027219Z digest=sha256:aa0a1f9b4077f0b3dd647c7b542464c72310390c459dd2a644e29f566cbd3fe8

Observation ca13f8f0-c01e-484b-ba2d-91f4692ec156 · outbound

This paper cites Generalization of hinging hyperplanes.IEEE Trans- actions on Information Theory, 51(12):4425–4431, 2005.

Toric geometry of ReLU neural networks Generalization of hinging hyperplanes.IEEE Trans- actions on Information Theory, 51(12):4425–4431, 2005

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.326935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:38.080459Z digest=sha256:91e6e7a60e80cbe1cc9a93fb7b9c7d234b6f0149435d9d0ca005b9e6354144d3

Observation 501ad357-6782-4053-9efd-9c84b4790d5d · outbound

This paper cites Tropical geometry of deep neu- ral networks.

Toric geometry of ReLU neural networks Tropical geometry of deep neu- ral networks

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:28:38.308663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T16:28:38.100097Z digest=sha256:72a3918cd83e93e2d3c742ef2c10574e81fb86844ec943244e6e9914b456fe28

Pith citing papers

Observation 991f3b3e-73ec-49fd-8071-6e7c284e6cc6 · inbound

On the fibers and semi-algebraicity of ReLU neuromanifolds cites this paper.

On the fibers and semi-algebraicity of ReLU neuromanifolds Toric geometry of ReLU neural networks

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:16:24.159341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-28T12:26:10.454497Z digest=sha256:4f5dd5d0ea06c026d89664d568bcafc73af6db747c003ddc12aa1fb6c627fce8