Paper Citation Record · LEDGER

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens

As of 16 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2507.05035.

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

pith.paper-citation-record.v1
2507.05035 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:40:36.599205Z

measured 47 of 47 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 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

47 of 47 outbound references displayed

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verified fuzzy16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34199f6a-2837-48d0-ba7c-cadc315131cf · outbound

This paper cites Neural Networks as Kernel Learners: The Silent Alignment Effect.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Neural Networks as Kernel Learners: The Silent Alignment Effect

Reference 1

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This paper cites The DeepMind JAX Ecosystem , 2020.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens The DeepMind JAX Ecosystem , 2020

Reference 2

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Observation bf443ac2-0e4f-4102-989f-20dbea4666a8 · outbound

This paper cites Explaining neural scaling laws.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Explaining neural scaling laws

Reference 3

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This paper cites D., Lajoie, G., Vincent, P., and Lacoste-Julien, S.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens D., Lajoie, G., Vincent, P., and Lacoste-Julien, S

Reference 4

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Observation 2eae836c-176a-4b70-a555-12629d524470 · outbound

This paper cites A foundation model for atomistic materials chemistry.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens A foundation model for atomistic materials chemistry

Reference 5

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Pehlevan, C

Reference 6

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Observation c546105f-c9e8-455f-b6fb-c6e109e0a37a · outbound

This paper cites On Lazy Training in Differentiable Programming.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens On Lazy Training in Differentiable Programming

Reference 7

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Observation 68d62b5e-98c5-44a7-a976-6a6058355613 · outbound

This paper cites and Wang, Z.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Wang, Z

Reference 8

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Observation 0bff6db7-bef3-4023-bebb-d40f307f348d · outbound

This paper cites K., Paul, M., Kharaghani, S., Roy, D.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens K., Paul, M., Kharaghani, S., Roy, D

Reference 9

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Observation c8f6de3c-d671-497a-8ba0-10f51c189c09 · outbound

This paper cites Disentangling feature and lazy training in deep neural networks.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Disentangling feature and lazy training in deep neural networks

Reference 10

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Observation c8ced368-6885-4e6d-9a05-2bae19426fa0 · outbound

This paper cites and Bengio, Y.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Bengio, Y

Reference 11

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Observation ba4ae497-719f-486f-bd5f-23228f5d19c2 · outbound

This paper cites Enough Coin Flips Can Make LLMs Act Bayesian.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Enough Coin Flips Can Make LLMs Act Bayesian

Reference 12

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Observation a2b25985-e7c3-40ec-91fa-354604ed3620 · outbound

This paper cites Delving Deep into Rectifiers : Surpassing Human - Level Performance on ImageNet Classification.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Delving Deep into Rectifiers : Surpassing Human - Level Performance on ImageNet Classification

Reference 13

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Observation e85869bf-bdf1-4a3e-aa83-a5d047940675 · outbound

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Unresolved cited work

Reference 14

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This paper cites Scaling Laws for Autoregressive Generative Modeling.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Scaling Laws for Autoregressive Generative Modeling

Reference 15

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Observation dab03078-7a51-4b91-8ae6-97d93b63005e · outbound

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Unresolved cited work

Reference 16

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Yau, H.-T

Reference 17

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Observation cac885d1-a04b-405d-ae7c-90021ba568a7 · outbound

This paper cites Learning Curve Theory.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Learning Curve Theory

Reference 18

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Observation 94065d16-4117-485b-873a-7185df497816 · outbound

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

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Neural Tangent Kernel : Convergence and Generalization in Neural Networks

Reference 19

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Observation d5b6bb4b-6d5d-4557-a28d-583a04f62d87 · outbound

This paper cites Scaling Laws for Neural Language Models.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Scaling Laws for Neural Language Models

Reference 20

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Observation 9b751f42-8eb9-4f21-8a74-e4f19f42dd82 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Adam: A Method for Stochastic Optimization

Reference 21

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Indelman, V

Reference 22

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Observation e211b2c5-13d4-4435-b704-1de780c4c7f5 · outbound

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Spannowsky, M

Reference 23

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Observation 72aa44e8-ce96-4b5e-b089-23026aa29a4f · outbound

This paper cites B., and Müller, K.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens B., and Müller, K

Reference 24

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Deep learning

Reference 25

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This paper cites Finite Versus Infinite Neural Networks : an Empirical Study.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Finite Versus Infinite Neural Networks : an Empirical Study

Reference 26

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Observation 18c3572f-3b3e-4cda-842c-e92f9177cab6 · outbound

This paper cites On the linearity of large non-linear models: when and why the tangent kernel is constant.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens On the linearity of large non-linear models: when and why the tangent kernel is constant

Reference 27

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Observation 2b4e8c52-293d-4a6b-9de7-af1a14ae192f · outbound

This paper cites Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit

Reference 28

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Observation 497bb98b-4b07-4f82-b7d6-9e26e88dc99e · outbound

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Neural Tangents: Fast and Easy Infinite Neural Networks in Python

Reference 29

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This paper cites What can linearized neural networks actually say about generalization? In Advances in Neural Information Processing Systems , volume 34, pp.\ 8998--9010.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens What can linearized neural networks actually say about generalization? In Advances in Neural Information Processing Systems , volume 34, pp.\ 8998--9010

Reference 30

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Observation fb94c23d-9262-4403-a2ce-37749aa106fb · outbound

This paper cites AstroCLIP: A Cross-Modal Foundation Model for Galaxies.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens AstroCLIP: A Cross-Modal Foundation Model for Galaxies

Reference 31

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This paper cites Neural networks trained with SGD learn distributions of increasing complexity.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Neural networks trained with SGD learn distributions of increasing complexity

Reference 32

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens A Constructive Prediction of the Generalization Error Across Scales

Reference 33

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Vetterli, M

Reference 34

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Kutyniok, G

Reference 35

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Observation 51325a34-0d4a-4414-a91c-74bbdfb192d8 · outbound

This paper cites A Theory of Neural Tangent Kernel Alignment and Its Influence on Training.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens A Theory of Neural Tangent Kernel Alignment and Its Influence on Training

Reference 36

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens and Kaplan, J

Reference 37

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Unresolved cited work

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens R., Martinez, T., and Giraud-Carrier, C

Reference 39

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This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Gemma 2: Improving Open Language Models at a Practical Size

Reference 40

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Towards a phenomenological understanding of neural networks: data

Reference 41

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This paper cites Collective variables of neural networks: empirical time evolution and scaling laws.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Collective variables of neural networks: empirical time evolution and scaling laws

Reference 42

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This paper cites Tensor Programs II: Neural Tangent Kernel for Any Architecture.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Tensor Programs II: Neural Tangent Kernel for Any Architecture

Reference 43

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Feature Learning in Infinite-Width Neural Networks

Reference 44

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens A Fine-Grained Spectral Perspective on Neural Networks

Reference 45

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Instance Regularization for Discriminative Language Model Pre -training

Reference 46

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Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens write newline

Reference 47

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Pith citing papers

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