Paper Citation Record · LEDGER

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries

As of 14 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2507.11366.

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

pith.paper-citation-record.v1
2507.11366 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:19:48.074078Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T14:22:06.385512Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d278a29-6988-45d0-a3e4-d3c932aab415 · outbound

This paper cites Last-iterate convergence rates for min-max optimization: Convergence of hamiltonian gradient descent and consensus optimization.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Last-iterate convergence rates for min-max optimization: Convergence of hamiltonian gradient descent and consensus optimization

Reference 1

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Observation 17be902c-9d3f-46ad-8a88-32d1c6bffb04 · outbound

This paper cites The equivalence of linear programs and zero-sum games.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries The equivalence of linear programs and zero-sum games

Reference 2

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Observation 6c668b6d-e43e-4f1c-ba54-7ffa47458164 · outbound

This paper cites $O\left(1/T\right)$ Time-Average Convergence in a Generalization of Multiagent Zero-Sum Games.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries $O\left(1/T\right)$ Time-Average Convergence in a Generalization of Multiagent Zero-Sum Games

Reference 3

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Observation dc58cba9-791f-40ce-b720-12fbf4e15132 · outbound

This paper cites Bailey, Gauthier Gidel, and Georgios Piliouras.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Bailey, Gauthier Gidel, and Georgios Piliouras

Reference 4

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Observation 91b17e0c-bb90-40d5-a3cb-46f342932011 · outbound

This paper cites Bailey and Georgios Piliouras.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Bailey and Georgios Piliouras

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:51.660975Z

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Observation 7f806d57-f135-49f8-9ad2-14df44c9916d · outbound

This paper cites Bailey and Georgios Piliouras.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Bailey and Georgios Piliouras

Reference 6

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Observation 864b354a-7a47-4c47-a628-4879fb095c48 · outbound

This paper cites Large scale gan training for high fidelity natural image synthesis.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Large scale gan training for high fidelity natural image synthesis

Reference 7

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Observation 174e3f01-07e2-4a2e-a9fe-471cd9358621 · outbound

This paper cites Zero-sum polymatrix games: A generalization of minmax.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Zero-sum polymatrix games: A generalization of minmax

Reference 8

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Observation 4dc2db81-4d2d-42ce-af10-07ca18161cea · outbound

This paper cites Accelerated algorithms for constrained nonconvex- nonconcave min-max optimization and comonotone inclusion.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Accelerated algorithms for constrained nonconvex- nonconcave min-max optimization and comonotone inclusion

Reference 9

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Observation 2c9c0d0a-0fb9-49ef-b1a4-22b6279fc080 · outbound

This paper cites Tikhonov regularization and the l-curve for large discrete ill-posed problems.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Tikhonov regularization and the l-curve for large discrete ill-posed problems

Reference 10

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Observation 2f8a2ae3-ecba-431f-924d-83040a4c290a · outbound

This paper cites Prediction, learning, and games.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Prediction, learning, and games

Reference 11

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Observation d58adf3a-751e-4ef4-a742-0b94c6023999 · outbound

This paper cites V ox2vox: 3d-gan for brain tumour segmentation.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries V ox2vox: 3d-gan for brain tumour segmentation

Reference 12

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Observation 506671ef-f635-41e2-a77d-ca11e49efcfd · outbound

This paper cites Last-iterate convergence: Zero-sum games and constrained min-max opti- mization.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Last-iterate convergence: Zero-sum games and constrained min-max opti- mization

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:51.580539Z

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Observation c7bee0b6-695a-455a-946d-3101da49a1ff · outbound

This paper cites Near-optimal no-regret algorithms for zero- sum games.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Near-optimal no-regret algorithms for zero- sum games

Reference 14

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Observation 364005e3-b9ee-49f3-afec-35c8cd61cd02 · outbound

This paper cites Near-optimal no-regret learning in general games, 2021.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Near-optimal no-regret learning in general games, 2021

Reference 15

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Observation b0b2565e-759f-4980-bb77-3dd13c6a2680 · outbound

This paper cites Training GANs with Optimism.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Training GANs with Optimism

Reference 16

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Observation 0b1ecc35-6ff2-41e3-b7c1-9f142a74d66c · outbound

This paper cites The limit points of (optimistic) gradient descent in min-max optimization.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries The limit points of (optimistic) gradient descent in min-max optimization

Reference 17

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Observation ead1d7f9-c76d-4095-b6d6-eba9a53360ca · outbound

This paper cites Multiagent online learning in time-varying games.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Multiagent online learning in time-varying games

Reference 18

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Observation f570a8ba-a0a6-4a17-8944-2b91a0281a1f · outbound

This paper cites Last iterate is slower than averaged iterate in smooth convex-concave saddle point problems.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Last iterate is slower than averaged iterate in smooth convex-concave saddle point problems

Reference 19

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Observation 6645f127-6d23-47ff-9b05-c2cc19496768 · outbound

This paper cites Generative adversarial nets.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Generative adversarial nets

Reference 20

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Observation 0495d800-737f-4511-ab3d-d315d4001e62 · outbound

This paper cites Long-time Energy Conservation , page 162–180.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Long-time Energy Conservation , page 162–180

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:50.109586Z

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Observation 99400669-d420-4303-8db6-d8aac17a005b · outbound

This paper cites Precomputed real-time texture synthesis with markovian generative adversarial networks.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Precomputed real-time texture synthesis with markovian generative adversarial networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:49.944147Z

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Observation 4a9ed950-1d49-4cfd-82d5-3d2de704d554 · outbound

This paper cites Cycles in adversarial regularized learning.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Cycles in adversarial regularized learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:49.774884Z

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Observation 6746570e-ed9b-4d2f-bac5-cd37638eb596 · outbound

This paper cites Convergence rate of O(1/k) for optimistic gradient and extragradient methods in smooth convex-concave saddle point problems.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Convergence rate of O(1/k) for optimistic gradient and extragradient methods in smooth convex-concave saddle point problems

Reference 24

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This paper cites an unresolved cited work.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Unresolved cited work

Reference 25

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Observation e964fd8b-a804-487d-9270-192cd337d430 · outbound

This paper cites Excessive gap technique in nonsmooth convex minimization.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Excessive gap technique in nonsmooth convex minimization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:49.392216Z

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Observation d5ac03a3-1b45-49b4-af02-1480d76c4fff · outbound

This paper cites An online mechanism for resource allocation in networks.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries An online mechanism for resource allocation in networks

Reference 27

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Observation 05d9295e-1c36-4839-9ba3-d6bb2123111a · outbound

This paper cites Twenty lectures on algorithmic game theory.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Twenty lectures on algorithmic game theory

Reference 28

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Observation 45afa6d2-bcb6-4aa3-8f59-6e5d59dbfebd · outbound

This paper cites On the Theory of Games of Strategy.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries On the Theory of Games of Strategy

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:48.930564Z

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Observation 69449838-6f2e-4b58-aea9-319b1265bd38 · outbound

This paper cites Accelerated algorithms for smooth convex-concave minimax problems with o (1/kˆ 2) rate on squared gradient norm.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Accelerated algorithms for smooth convex-concave minimax problems with o (1/kˆ 2) rate on squared gradient norm

Reference 30

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Observation cbb436bc-a83d-485a-a7fa-5c9046c3e84c · outbound

This paper cites Deform-GAN:An Unsupervised Learning Model for Deformable Registration.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Deform-GAN:An Unsupervised Learning Model for Deformable Registration

Reference 31

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Observation 822f8d48-c61d-4f4b-b6a8-9dba3aebdf36 · outbound

This paper cites Bayesian Conditional GAN for MRI Brain Image Synthesis.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries Bayesian Conditional GAN for MRI Brain Image Synthesis

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:19:48.230776Z

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Observation 8b4b3802-3916-4cad-ba92-6c40dfb95fb5 · outbound

This paper cites 3d high resolution generative deep-learning network for fluorescence microscopy imaging.

Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries 3d high resolution generative deep-learning network for fluorescence microscopy imaging

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:19:48.690136Z

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Pith citing papers

Observation 336c6131-7247-498a-b84f-c6838339de97 · inbound

Implicit Midpoint Gradient Descent: Fast and Learning rate free convergence for Zero-Sum Games cites this paper.

Implicit Midpoint Gradient Descent: Fast and Learning rate free convergence for Zero-Sum Games Characterizing Nash Equilibria in Zero-Sum Games: A Physics-Inspired, Parallelizable Approach with a Linear Number of Gradient Queries

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T14:22:06.385512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.