Paper Citation Record · LEDGER

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer

As of 22 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2605.29713.

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

pith.paper-citation-record.v1
2605.29713 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T08:53:49.780277Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

43 of 43 outbound references displayed

verified exact2
verified fuzzy0
unresolved41
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e16e4b05-5eee-462f-af03-aba22eb3825f · outbound

This paper cites A Learning Algo- rithm for Boltzmann Machines.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer A Learning Algo- rithm for Boltzmann Machines

Reference 1

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Observation 9a8685b3-2e6a-4fd4-a1d1-f3eb2aab4fab · outbound

This paper cites Wasserstein Generative Ad- versarial Networks.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Wasserstein Generative Ad- versarial Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation b8741fae-013d-47d7-b553-aee3557d04a6 · outbound

This paper cites Neural Networks and Principal Component Analysis: Learning from Examples Without Local Minima.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Neural Networks and Principal Component Analysis: Learning from Examples Without Local Minima

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Unavailable: canonical work link unavailable.

Observation 8ea090e0-396d-48d9-9549-55c2c920f675 · outbound

This paper cites an unresolved cited work.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Unavailable: canonical work link unavailable.

Observation f86015fd-f539-4edb-a169-102b1283749b · outbound

This paper cites From Classical Probabilistic Latent Variable Models to Modern Generative AI: A Unified Perspective.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer From Classical Probabilistic Latent Variable Models to Modern Generative AI: A Unified Perspective

Reference 5

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Source-reported events for the cited work

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Observation bfdea068-5524-4080-a4a0-537b94200c6d · outbound

This paper cites SSRN preprint, originally posted May 2025.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer SSRN preprint, originally posted May 2025

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bc5b8ba-2611-4e02-92fa-753fbb8e6804 · outbound

This paper cites Maximum Likelihood from Incomplete Data via the EM Algorithm.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Maximum Likelihood from Incomplete Data via the EM Algorithm

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation ceed111d-d7b1-4d01-b8ca-cd1eccb752c1 · outbound

This paper cites NICE: Non-linear Independent Components Estimation.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer NICE: Non-linear Independent Components Estimation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

Source-reported events for the cited work

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Observation adeb41f3-3ef1-410d-8d77-005e6f77f413 · outbound

This paper cites Density Estimation using Real NVP.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Density Estimation using Real NVP

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Unavailable: canonical work link unavailable.

Observation 2aeee861-dcbc-4142-ad80-018169e96e3d · outbound

This paper cites Evans.Partial Differential Equations.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Evans.Partial Differential Equations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7653714e-2c5a-4e57-b6f1-0383a606b89e · outbound

This paper cites MADE: Masked Autoencoder for Distribution Estimation.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer MADE: Masked Autoencoder for Distribution Estimation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation fc7e3790-c20a-4271-b87a-14b6d62cab78 · outbound

This paper cites Generative Adversarial Nets.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Generative Adversarial Nets

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 28561d48-8421-4561-8b04-c3538df76010 · outbound

This paper cites Improved Training of Wasserstein GANs.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Improved Training of Wasserstein GANs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation a718579d-5bbc-478d-9e80-0caa31693598 · outbound

This paper cites beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 154f9330-cff3-4149-8220-3ea0d10128ff · outbound

This paper cites Reducing the Dimensionality of Data with Neural Networks.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Reducing the Dimensionality of Data with Neural Networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation e07cb788-6060-4e17-b312-024222c34f41 · outbound

This paper cites Denoising Diffusion Probabilistic Mod- els.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Denoising Diffusion Probabilistic Mod- els

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation cfc7a82d-97be-40ee-90db-eff88ca1da59 · outbound

This paper cites Neural Networks and Physical Systems with Emergent Collective Computational Abilities.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Neural Networks and Physical Systems with Emergent Collective Computational Abilities

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 6f678bfa-2492-4dc6-9c0b-ce5d74abab9f · outbound

This paper cites Analysis of a Complex of Statistical Variables into Principal Com- ponents.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Analysis of a Complex of Statistical Variables into Principal Com- ponents

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 60681628-e15b-47b4-8cda-1cac4be62dfc · outbound

This paper cites Estimation of Non-Normalized Statistical Models by Score Match- ing.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Estimation of Non-Normalized Statistical Models by Score Match- ing

Reference 19

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Observation 3f4ed988-c3c5-4091-87c7-5e656cc40697 · outbound

This paper cites Principal Component Analysis: A Review and Re- cent Developments.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Principal Component Analysis: A Review and Re- cent Developments

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation e0dfbf3c-b916-409b-a1d9-1691d9c35079 · outbound

This paper cites Auto-Encoding Variational Bayes.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Auto-Encoding Variational Bayes

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation cc092451-2489-4c9c-ace2-873879196eae · outbound

This paper cites An Introduction to Variational Autoencoders.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer An Introduction to Variational Autoencoders

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation c977c899-944d-423d-982f-ccb8847998e5 · outbound

This paper cites Glow: Generative Flow with Invertible 1x1 Convolutions.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Glow: Generative Flow with Invertible 1x1 Convolutions

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 566924f4-0224-4adf-bf9a-1fa97463185b · outbound

This paper cites A Tutorial on Energy-Based Learning.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer A Tutorial on Energy-Based Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation b0277818-d442-4656-9253-c21a3911a1d4 · outbound

This paper cites Flow Matching for Generative Modeling.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Flow Matching for Generative Modeling

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation b61dae10-4c14-43f1-bce6-70716038f709 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 26

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Observation 1dbd3da2-eec0-4835-bcff-daec62d66e1d · outbound

This paper cites Murphy.Machine Learning: A Probabilistic Perspective.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Murphy.Machine Learning: A Probabilistic Perspective

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation de60a004-897e-4d53-a498-03797bca98dc · outbound

This paper cites Improved Denoising Diffusion Prob- abilistic Models.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Improved Denoising Diffusion Prob- abilistic Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 74784a08-3ff0-4729-b298-e4273bee34e3 · outbound

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The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 2fc5e6f9-8884-4708-8b28-c2cc84485545 · outbound

This paper cites Pixel Recurrent Neural Networks.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Pixel Recurrent Neural Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 4e4aae5e-c419-4ed3-bd33-f48235e88d73 · outbound

This paper cites WaveNet: A Generative Model for Raw Audio.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer WaveNet: A Generative Model for Raw Audio

Reference 31

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Source-reported events for the cited work

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Observation eda4de9a-78f9-4f89-80c4-d3a27e90ab6e · outbound

This paper cites Normalizing Flows for Probabilistic Modeling and Infer- ence.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Normalizing Flows for Probabilistic Modeling and Infer- ence

Reference 32

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Observation b7fca711-e955-492c-b221-cbcdb336689b · outbound

This paper cites On Lines and Planes of Closest Fit to Systems of Points in Space.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer On Lines and Planes of Closest Fit to Systems of Points in Space

Reference 33

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Observation 1c794069-d76e-459b-b872-0ab5f454d9ed · outbound

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The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Variational Inference with Normaliz- ing Flows

Reference 34

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Observation 403e4452-40ac-4dc6-ba76-1bec882974b3 · outbound

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The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Stochastic Backprop- agation and Approximate Inference in Deep Generative Models

Reference 35

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Observation 6eb4b1c1-f753-480e-bc44-7097d8288c6b · outbound

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The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Unresolved cited work

Reference 36

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Observation 51309cbd-f5a0-4710-942c-831aea2cab8f · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Ther- modynamics.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Deep Unsupervised Learning using Nonequilibrium Ther- modynamics

Reference 37

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Observation 71127ad6-1528-4b04-a0b9-fab961b5e2a0 · outbound

This paper cites Generative Modeling by Estimating Gradients of the Data Distribution.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Generative Modeling by Estimating Gradients of the Data Distribution

Reference 38

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Observation c34828f4-88ff-4fed-9ed9-760f0da28c07 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Score-Based Generative Modeling through Stochastic Differential Equations

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 63ea03a2-d96a-43ce-9b49-1e9da54dd491 · outbound

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The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Consistency Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Observation 27347062-57b5-410e-8ab9-f9c5c7fcaac0 · outbound

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The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Unresolved cited work

Reference 41

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Observation 9b6a0f64-a6e8-43d4-b777-0c0623566185 · outbound

This paper cites Probabilistic Principal Component Analysis.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer Probabilistic Principal Component Analysis

Reference 42

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Observation 5ed74a10-ec55-48ae-a783-812f6031733e · outbound

This paper cites A Connection Between Score Matching and Denoising Autoencoders.

The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer A Connection Between Score Matching and Denoising Autoencoders

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-29T08:53:49.780277Z

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Pith citing papers

No inbound Pith citation observations are available.