Paper Citation Record · LEDGER

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games

As of 10 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.06514.

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

pith.paper-citation-record.v1
2607.06514 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-08T03:17:09.608451Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

46 of 46 outbound references displayed

verified exact2
verified fuzzy28
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 61857ba0-41cc-48c8-b28a-190f9125098b · outbound

This paper cites Nature , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Nature , volume=

Reference 1

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Observation b3e261d2-5787-46b0-8185-09747a2a6b27 · outbound

This paper cites CoGrid & the Multi-User Gymnasium: A Framework for Multi-Agent Experimentation.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games CoGrid & the Multi-User Gymnasium: A Framework for Multi-Agent Experimentation

Reference 2

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Observation 5c700bd5-8a52-40e5-9923-ccfed0c24478 · outbound

This paper cites nature , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games nature , volume=

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.179685Z

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Observation 9d2a85aa-0f5f-442d-80bc-c59ac6c560af · outbound

This paper cites Science , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Science , volume=

Reference 4

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Observation 4f035eef-7dd1-4219-9ce5-f1e1a664c9e5 · outbound

This paper cites A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games

Reference 5

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Observation 85a40299-c110-40e7-9547-4838cfc467b5 · outbound

This paper cites Advances in neural information processing systems , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Advances in neural information processing systems , volume=

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.200202Z

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Observation ddae4cab-c4d6-495f-975b-74a8cfcd080f · outbound

This paper cites Reevaluating Policy Gradient Methods for Imperfect-Information Games.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Reevaluating Policy Gradient Methods for Imperfect-Information Games

Reference 7

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Observation 48516bc5-2e29-418c-9d54-23f297a52edf · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 8

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Observation 5926f81e-789f-435e-a37d-bada7b336bdf · outbound

This paper cites International conference on machine learning , pages=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games International conference on machine learning , pages=

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.200028Z

Source-reported events for the cited work

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Observation bfc51e13-8bdd-4440-806d-7a7c91aacd4f · outbound

This paper cites Advances in neural information processing systems , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Advances in neural information processing systems , volume=

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.195467Z

Source-reported events for the cited work

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Observation 531a8535-f988-414d-811c-2cedb2f5c5f9 · outbound

This paper cites Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 11

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Observation 568a338a-ce4f-4bd7-b9da-fb4b4d52ed5d · outbound

This paper cites EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games

Reference 12

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Observation 663810ef-5502-42f2-8706-affb2ed7b2ed · outbound

This paper cites International conference on machine learning , pages=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games International conference on machine learning , pages=

Reference 13

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Observation fee86fc1-268c-4449-afde-bcd9c2db1f0b · outbound

This paper cites Goal-Conditioned Reinforcement Learning: Problems and Solutions.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Goal-Conditioned Reinforcement Learning: Problems and Solutions

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T03:24:28.837788Z

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Observation e71f0d2f-1791-4d77-8004-1cd0b121fe8e · outbound

This paper cites Approximate exploitability: Learning a best response in large games.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Approximate exploitability: Learning a best response in large games

Reference 15

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Observation eaf7e2c4-ef0e-4012-946f-ff12009e3349 · outbound

This paper cites Advances in neural information processing systems , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Advances in neural information processing systems , volume=

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.203835Z

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Observation 0b703657-d6d5-4973-8220-21516a76a33a · outbound

This paper cites Other-play.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Other-play

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.207593Z

Source-reported events for the cited work

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Observation e062d8b7-7761-435b-a46b-b5b77e235dd6 · outbound

This paper cites International Conference on Learning Representations , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games International Conference on Learning Representations , volume=

Reference 18

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Observation 98bb5eb4-9452-4d72-a7de-9f22200c161d · outbound

This paper cites Any-Play: An Intrinsic Augmentation for Zero-Shot Coordination.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Any-Play: An Intrinsic Augmentation for Zero-Shot Coordination

Reference 19

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Observation 7c59160f-48fe-4236-a9fd-2b2171f475e0 · outbound

This paper cites Advances in neural information processing systems , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Advances in neural information processing systems , volume=

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.190434Z

Source-reported events for the cited work

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Observation cca88eac-2ef0-4173-b03a-46ba4d00fdee · outbound

This paper cites Proximal Policy Optimization Algorithms.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Proximal Policy Optimization Algorithms

Reference 21

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Observation e88a76f5-7bf3-4593-9a8c-44c502df78a8 · outbound

This paper cites IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

Reference 22

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Observation c127c351-d9b4-4aff-adf3-e809dc654856 · outbound

This paper cites International conference on machine learning , pages=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games International conference on machine learning , pages=

Reference 23

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Observation 308938b9-8c13-4f87-8ab6-e56a36d18b53 · outbound

This paper cites nature , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games nature , volume=

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.205708Z

Source-reported events for the cited work

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Observation edd021f7-3c05-485f-94e5-33139f20ce07 · outbound

This paper cites Controllable Complementarity: Subjective Preferences in Human-AI Collaboration.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Controllable Complementarity: Subjective Preferences in Human-AI Collaboration

Reference 25

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Observation 670c3d7f-0c10-4616-b2b2-a494f3daf829 · outbound

This paper cites Neural Computation MIT-Press , year=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Neural Computation MIT-Press , year=

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.188074Z

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Observation 0fdcda19-532d-4581-b43d-ab2c91a1a925 · outbound

This paper cites Deep Reinforcement Learning from Self-Play in Imperfect-Information Games.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

Reference 27

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Observation 8f8875be-9b69-42c2-b70d-aff759b14686 · outbound

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FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Unresolved cited work

Reference 28

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Observation 4eae10d5-c07f-4c2b-9a03-6d21553be121 · outbound

This paper cites Unity: A General Platform for Intelligent Agents.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Unity: A General Platform for Intelligent Agents

Reference 29

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Observation 9e0535c7-3629-404b-a4e1-3564a9968405 · outbound

This paper cites Comparison of Reaction Time Between eSports Players of Different Genres and Sportsmen , journal =.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Comparison of Reaction Time Between eSports Players of Different Genres and Sportsmen , journal =

Reference 30

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Observation 3d4ec283-cf4f-4afc-8e9c-ff1be633fd08 · outbound

This paper cites and Black, Benjamin and Grammel, Nathaniel and Jayakumar, Mario and Hari, Ananth and Sullivan, Ryan and Santos, Luis S.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games and Black, Benjamin and Grammel, Nathaniel and Jayakumar, Mario and Hari, Ananth and Sullivan, Ryan and Santos, Luis S

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.206203Z

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Observation 5744917f-261e-4246-851e-3526ab98adbc · outbound

This paper cites OpenSpiel: A Framework for Reinforcement Learning in Games.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games OpenSpiel: A Framework for Reinforcement Learning in Games

Reference 32

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This paper cites 2020 , howpublished =.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games 2020 , howpublished =

Reference 33

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Observation 3ef1c61b-9663-4a58-837f-e4ce56463fc4 · outbound

This paper cites 2020 , howpublished =.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games 2020 , howpublished =

Reference 34

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Observation 68d025f1-7bb2-4030-80fa-f5ecb0686abf · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume =.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Proceedings of the AAAI Conference on Artificial Intelligence , volume =

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.211754Z

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Observation a740615e-fe21-418e-936d-fb29a645815f · outbound

This paper cites EvoJAX: Hardware-Accelerated Neuroevolution.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games EvoJAX: Hardware-Accelerated Neuroevolution

Reference 36

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Observation edffd555-0fd4-4700-a151-1ebd4fc45daf · outbound

This paper cites Advances in neural information processing systems , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Advances in neural information processing systems , volume=

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.215975Z

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Observation 9c51d207-77eb-4100-a29b-15cd662fca9e · outbound

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FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Unresolved cited work

Reference 38

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Source-reported events for the cited work

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Observation da7b396b-efb3-4ef1-ba78-066e3a453c96 · outbound

This paper cites Gotta Learn Fast: A New Benchmark for Generalization in.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Gotta Learn Fast: A New Benchmark for Generalization in

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.198259Z

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Observation 11d33111-170d-42b7-8fa8-216a554d22f8 · outbound

This paper cites 2022 IEEE Conference on Games (CoG) , pages=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games 2022 IEEE Conference on Games (CoG) , pages=

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.163276Z

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Observation dd42d744-df23-4248-987b-38378cc6f4f4 · outbound

This paper cites 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE) , pages=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE) , pages=

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.178367Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4743ca8b-8156-4a90-b826-f1fc40cb3e12 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , articleno =.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Proceedings of the 41st International Conference on Machine Learning , articleno =

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.202131Z

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Observation dff0f3a0-da67-45f8-9671-57cda3cf86b0 · outbound

This paper cites Creating Pro-Level.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Creating Pro-Level

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.201862Z

Source-reported events for the cited work

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Observation be141abf-3847-4764-8df6-9ff9b25ba574 · outbound

This paper cites and Tenenbaum, Joshua B.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games and Tenenbaum, Joshua B

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.218070Z

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Observation 8c425563-8c1c-4019-9498-53fe880d4f7c · outbound

This paper cites IEEE Transactions on Games , volume=.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games IEEE Transactions on Games , volume=

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.189981Z

Source-reported events for the cited work

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Observation 4797f48d-2ed1-4b2e-969d-0b2e5da929e6 · outbound

This paper cites 2018 IEEE Conference on Computational Intelligence and Games (CIG) , pages =.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games 2018 IEEE Conference on Computational Intelligence and Games (CIG) , pages =

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T03:24:29.183090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.