Paper Citation Record · LEDGER

All in One: Generative Modeling as Mean-Field Game Design

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.23026.

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

pith.paper-citation-record.v1
2607.23026 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:54:20.036647Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

30 of 30 outbound references displayed

verified exact0
verified fuzzy0
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07312171-4f99-4b87-a156-917df27b5a4d · outbound

This paper cites an unresolved cited work.

All in One: Generative Modeling as Mean-Field Game Design Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:17.772053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04cd1231-400a-44fc-8be6-663b5ca99932 · outbound

This paper cites Albergo, Nicholas M.

All in One: Generative Modeling as Mean-Field Game Design Albergo, Nicholas M

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:17.811146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 337cf17b-7542-4709-9cd0-39fec8c73edd · outbound

This paper cites an unresolved cited work.

All in One: Generative Modeling as Mean-Field Game Design Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:17.885380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79587aed-049c-45c9-899a-5075fc64e159 · outbound

This paper cites Learning dual mean field games on graphs.

All in One: Generative Modeling as Mean-Field Game Design Learning dual mean field games on graphs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:17.963612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a51ade03-70ee-49a7-acd4-b3dc12dcce88 · outbound

This paper cites SVGD as a kernelized wasserstein gradient flow of the chi-squared divergence.Advances in Neural Information Processing Systems, 2020.

All in One: Generative Modeling as Mean-Field Game Design SVGD as a kernelized wasserstein gradient flow of the chi-squared divergence.Advances in Neural Information Processing Systems, 2020

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.029257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e416c08b-ea27-4b00-ac1e-71bc8051b75d · outbound

This paper cites nflows: normalizing flows in PyTorch, 2020.

All in One: Generative Modeling as Mean-Field Game Design nflows: normalizing flows in PyTorch, 2020

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.115106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eca1d49d-6262-477e-be09-3fa7310abe10 · outbound

This paper cites an unresolved cited work.

All in One: Generative Modeling as Mean-Field Game Design Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.215226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20492cf0-d1aa-4440-bf5f-9a0cefaa8238 · outbound

This paper cites Learning mean-field games.

All in One: Generative Modeling as Mean-Field Game Design Learning mean-field games

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.325885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21189f99-4a81-4d75-a147-814019b73345 · outbound

This paper cites Generative adversarial imitation learning.

All in One: Generative Modeling as Mean-Field Game Design Generative adversarial imitation learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.437632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36342506-f246-4873-a0f9-e32274976465 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020.

All in One: Generative Modeling as Mean-Field Game Design Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.539961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa076ae3-3cbd-46b7-96d4-70b7e367a0d6 · outbound

This paper cites Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations.

All in One: Generative Modeling as Mean-Field Game Design Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.591111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62c3b3c4-9d54-40d3-a4e7-a7596db59674 · outbound

This paper cites Malhamé, and Peter E.

All in One: Generative Modeling as Mean-Field Game Design Malhamé, and Peter E

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.653072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a7a0e21-bdc3-42a3-a084-2c41a1c34f70 · outbound

This paper cites Mean field games.Japanese Journal of Mathematics, 2(1):229–260, 2007.

All in One: Generative Modeling as Mean-Field Game Design Mean field games.Japanese Journal of Mathematics, 2(1):229–260, 2007

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.696582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c8df105-1e91-4ee1-bab1-103f1616f5a2 · outbound

This paper cites Learning in Mean Field Games: A Survey.

All in One: Generative Modeling as Mean-Field Game Design Learning in Mean Field Games: A Survey

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.750839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 836ca569-0481-4c3c-8ada-fb4ad8563e38 · outbound

This paper cites an unresolved cited work.

All in One: Generative Modeling as Mean-Field Game Design Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.780756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0410a0a1-ab48-464d-b605-1aca12d9225c · outbound

This paper cites Let us build bridges: Understanding and extending diffusion generative models.

All in One: Generative Modeling as Mean-Field Game Design Let us build bridges: Understanding and extending diffusion generative models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.890091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dd65e16-e409-42e2-a670-10aed58a5cdd · outbound

This paper cites Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport and diffu- sions.International Conference on Machine Learning, 2019.

All in One: Generative Modeling as Mean-Field Game Design Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport and diffu- sions.International Conference on Machine Learning, 2019

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:18.981942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddabf6a8-f959-4f61-a58f-a677c930ee1e · outbound

This paper cites an unresolved cited work.

All in One: Generative Modeling as Mean-Field Game Design Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.075961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40ba5b3d-fef9-4e69-a709-ba273c4c613a · outbound

This paper cites Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning.Science, 365(6457), 2019.

All in One: Generative Modeling as Mean-Field Game Design Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning.Science, 365(6457), 2019

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.139176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52c4dc9f-f917-4262-b27c-b23b4c9e857b · outbound

This paper cites OT-Flow: Fast and accurate continuous normalizing flows via optimal transport.AAAI Conference on Artificial Intelligence, 2021.

All in One: Generative Modeling as Mean-Field Game Design OT-Flow: Fast and accurate continuous normalizing flows via optimal transport.AAAI Conference on Artificial Intelligence, 2021

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.234889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c45b9ff-17a1-4be3-a8ae-15b77e305202 · outbound

This paper cites Fictitious play for mean field games: Continuous time analysis and applications.

All in One: Generative Modeling as Mean-Field Game Design Fictitious play for mean field games: Continuous time analysis and applications

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.322277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3af16d52-25cb-40c7-84db-45994edb91a2 · outbound

This paper cites On imitation in mean-field games.

All in One: Generative Modeling as Mean-Field Game Design On imitation in mean-field games

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.385321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5b4879a-ad6a-42f2-9b41-8ab7ad2a54c6 · outbound

This paper cites Osher, Wuchen Li, Levon Nurbekyan, and Samy Wu Fung.

All in One: Generative Modeling as Mean-Field Game Design Osher, Wuchen Li, Levon Nurbekyan, and Samy Wu Fung

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.446286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8762c09-4360-4f27-90f2-aaee0db009b4 · outbound

This paper cites Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole.

All in One: Generative Modeling as Mean-Field Game Design Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.543013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8af2ca7-a6e4-4e06-b380-95f61b5cbe22 · outbound

This paper cites normflows: A PyTorch package for nor- malizing flows, 2023.

All in One: Generative Modeling as Mean-Field Game Design normflows: A PyTorch package for nor- malizing flows, 2023

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.660790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5374b9ea-9f79-4bcb-bb04-c5064cfc7729 · outbound

This paper cites Diffusers: State-of-the-art diffusion models, 2022.

All in One: Generative Modeling as Mean-Field Game Design Diffusers: State-of-the-art diffusion models, 2022

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.728612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10a221ac-3d00-422f-b0bf-993f1be84d26 · outbound

This paper cites A mean-field games laboratory for generative modeling.

All in One: Generative Modeling as Mean-Field Game Design A mean-field games laboratory for generative modeling

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.800240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9288c8c1-215e-4b83-a94c-df3861a86f9d · outbound

This paper cites Stochastic semi-gradient descent for learning mean field games with population-aware function approximation.

All in One: Generative Modeling as Mean-Field Game Design Stochastic semi-gradient descent for learning mean field games with population-aware function approximation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.882242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa16ff3e-9397-494e-82d1-48782b80ef42 · outbound

This paper cites Graphon mean field games with a representative player: Analysis and learning algorithm.

All in One: Generative Modeling as Mean-Field Game Design Graphon mean field games with a representative player: Analysis and learning algorithm

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:19.981189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 400ccdda-7d18-4efe-8aeb-b88e4536cf22 · outbound

This paper cites Ziebart, Andrew Maas, J.

All in One: Generative Modeling as Mean-Field Game Design Ziebart, Andrew Maas, J

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T03:54:20.036647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.