Paper Citation Record · LEDGER

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations

As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2607.13749.

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

pith.paper-citation-record.v1
2607.13749 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:55:35.449529Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy0
unresolved16
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d3fbb2a3-dcba-494d-ac74-d11643ead342 · outbound

This paper cites A Basin-Selection Perspective on Grokking via Singular Learning Theory.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations A Basin-Selection Perspective on Grokking via Singular Learning Theory

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.536326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c19d39ae-6b5f-44b6-a505-ce65782ce3c1 · outbound

This paper cites Approximation by superpositions of a sigmoidal function.Mathematics of Control, Signals and Systems, 2(4):303–314, 1989.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Approximation by superpositions of a sigmoidal function.Mathematics of Control, Signals and Systems, 2(4):303–314, 1989

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.588741Z

Source-reported events for the cited work

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Observation 97f906b3-6a31-4418-937f-376213a08d6e · outbound

This paper cites Grokking Modular Polynomials.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Grokking Modular Polynomials

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.633765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5faf7b10-eae9-4ce5-9251-90042a46595c · outbound

This paper cites Grokking modular arithmetic.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Grokking modular arithmetic

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.700633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2158df39-5a22-4b11-9880-3bc0fa2e0e5f · outbound

This paper cites Approximation capabilities of multilayer feedforward networks.Neural Networks, 4(2):251–257, 1991.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Approximation capabilities of multilayer feedforward networks.Neural Networks, 4(2):251–257, 1991

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.774458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ee5fc7b-1515-4c0e-9e75-e1db86041400 · outbound

This paper cites Neural Tangent Kernel: Convergence and Generalization in Neural Networks.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.829928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2af7241a-8ae7-443f-ae4b-acc0d453ebd5 · outbound

This paper cites On the Expressive Power of Deep Polynomial Neural Networks.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations On the Expressive Power of Deep Polynomial Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.903371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85db5dd2-81a7-4cae-8a15-34577a7c9cf8 · outbound

This paper cites Grokking as the Transition from Lazy to Rich Training Dynamics.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Grokking as the Transition from Lazy to Rich Training Dynamics

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:34.969405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a5a9886-367e-44fb-9646-209d901002fb · outbound

This paper cites Towards Understanding Grokking: An Effective Theory of Representation Learning.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Towards Understanding Grokking: An Effective Theory of Representation Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.029615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e792b11f-1b9a-45c7-97ed-cf35d403ffef · outbound

This paper cites Progress measures for grokking via mechanistic interpretability.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Progress measures for grokking via mechanistic interpretability

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.092618Z

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Observation 3d1e8ebf-baac-45e4-bd82-82f6efa22fda · outbound

This paper cites Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.152336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a16fc2b-97d2-4334-b1c8-2e2d55202b1a · outbound

This paper cites Grokking as a First Order Phase Transition in Two Layer Networks.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Grokking as a First Order Phase Transition in Two Layer Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.218736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac7b0e1b-0025-4d75-987e-bff841444a72 · outbound

This paper cites Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.281740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efb703b4-9d4e-4776-ad9f-117dbb85d85e · outbound

This paper cites Benefits of depth in neural networks.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Benefits of depth in neural networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.331715Z

Source-reported events for the cited work

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Observation 960fef8a-1f6c-44e8-8264-38275e0c8674 · outbound

This paper cites Deep Complex Networks.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Deep Complex Networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.394380Z

Source-reported events for the cited work

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Observation 18d1b619-01a7-42fc-bbeb-5f8bea9a923f · outbound

This paper cites Grokking phase transitions in learning local rules with gradient descent.

Algebraic Representability as the Limiting Regime of Grokking: An Exactly Solvable Model with Holomorphic Activations Grokking phase transitions in learning local rules with gradient descent

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:35.449529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.