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Paper Citation Record · LEDGER

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization

As of 15 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 3 inbound Pith citation observations for arXiv:2607.27035.

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

pith.paper-citation-record.v1
2607.27035 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T13:10:40.415459Z

measured 97 of 97 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:42:08.768689Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:22:29.075117Z

Reference resolution

94 of 94 outbound references displayed

  • verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d90f006-5ff8-458c-b0a7-fc96de7a73b1 · outbound

This paper cites Science , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Science , volume=

Reference 1

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source=arxiv_source observed=2026-07-30T13:10:39.102145Z digest=sha256:98d7a06cf6ea984386f52efb8960363680bd81ae441f46e3a14261330ceedd00

Observation ec895630-e407-46a4-96d7-97d76fb938e9 · outbound

This paper cites Science , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Science , volume=

Reference 2

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source=arxiv_source observed=2026-07-30T13:10:39.162950Z digest=sha256:c4798654c7290218254bddd0be8c5d67f22c6cb84937ff40060c8f373f1814e6

Observation ff905a81-8197-40bb-8476-d047783d44e5 · outbound

This paper cites Science , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Science , volume=

Reference 3

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source=arxiv_source observed=2026-07-30T13:10:39.226021Z digest=sha256:cf75c344f587b41efb3cf5f610577d22c60c8dc1163ecd6d0084c3f69cf56392

Observation 87455fb4-2bf8-448e-9845-d6d5e7c06d1a · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in neural information processing systems , volume=

Reference 4

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source=arxiv_source observed=2026-07-30T13:10:39.228844Z digest=sha256:79a1ddaf9b315f2b5965171c7888443eeb7d6deb5049be0d95ecc4c91464af2d

Observation 6f7767a3-6fb6-4f26-a2b5-d9e889fe83e3 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in neural information processing systems , volume=

Reference 5

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source=arxiv_source observed=2026-07-30T13:10:39.301011Z digest=sha256:ccc3fe4df611a3b18d46d8a157e3eebfac31b028ba1272fb1c6acfce17ad18e4

Observation 4b83b821-bfe8-4cd6-8003-bda4202942b7 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 6

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source=arxiv_source observed=2026-07-30T13:10:39.418837Z digest=sha256:fb0b7d383cc35d54ce01cefa680c2a1f70c4b4ebb1c911ee271ccbccdedeb530

Observation 1800ea2c-d8f9-4004-b0c8-8112a466b0fd · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in neural information processing systems , volume=

Reference 7

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source=arxiv_source observed=2026-07-30T13:10:39.531642Z digest=sha256:f24b38083b0f61915b95253cba2f92b3bfa4ba04c93604a15d3f76fac759182e

Observation 0a58a376-6b97-466b-97e1-8e0e74035f94 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 8

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Observation f4faaaec-20b4-44b0-8c1b-dc436fe2f8f3 · outbound

This paper cites International Conference on Machine Learning , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization International Conference on Machine Learning , pages=

Reference 9

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source=arxiv_source observed=2026-07-30T13:10:39.775000Z digest=sha256:16d10695400e1ed96050629d46e983745f53e83110c0355d2a6af2e723e986d5

Observation 95d58b13-a98a-4512-aa4c-e81a6c3dd4c4 · outbound

This paper cites The Eleventh International Conference on Learning Representations , year=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization The Eleventh International Conference on Learning Representations , year=

Reference 10

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source=arxiv_source observed=2026-07-30T13:10:39.973587Z digest=sha256:bd0d7c09233775a7509157ee97bb60f23414630170fbd73ae7e1989e361c13ff

Observation e79c731d-09dd-4891-978d-2daec22d97ad · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization International conference on machine learning , pages=

Reference 11

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source=arxiv_source observed=2026-07-30T13:10:39.988015Z digest=sha256:9317877eb421c6776632d7a5091075bfaedfb53e350cd56f2a6f0f5e6236229d

Observation 192a6ce2-ca62-4ee0-844b-ab7f680b04ba · outbound

This paper cites International Conference on Machine Learning , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization International Conference on Machine Learning , pages=

Reference 12

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source=arxiv_source observed=2026-07-30T13:10:39.991021Z digest=sha256:f46093df01b105beaf99a90bc482e02eb922acf9ce22816562acb16e89bfde80

Observation 86d98336-e7f0-49fe-8d9f-d76ba8719acb · outbound

This paper cites 1992 , publisher=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization 1992 , publisher=

Reference 13

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source=arxiv_source observed=2026-07-30T13:10:39.993871Z digest=sha256:b2fde571341e8e8b56d5d1dfd9f14fb7fdbb588fbed8efcc2f3ad5d7392c575b

Observation 46b1a284-c5ae-420e-a2e4-35c966adb53d · outbound

This paper cites SIAM Journal on Numerical Analysis , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization SIAM Journal on Numerical Analysis , volume=

Reference 14

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Observation bc5d236a-3224-4540-b098-d0e919fc057c · outbound

This paper cites SIAM Journal on Numerical Analysis , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization SIAM Journal on Numerical Analysis , volume=

Reference 15

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Observation 3bf87298-d09f-48af-8b99-e476f353d897 · outbound

This paper cites USSR Computational mathematics and mathematical physics , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization USSR Computational mathematics and mathematical physics , volume=

Reference 16

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Observation b5c49460-f78f-411f-a5f3-f5bac8941a0a · outbound

This paper cites Numerische Mathematik , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Numerische Mathematik , volume=

Reference 17

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Observation 54df5664-36cd-4eb2-86f3-062d54341947 · outbound

This paper cites The Annals of Mathematical Statistics , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization The Annals of Mathematical Statistics , volume=

Reference 18

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source=arxiv_source observed=2026-07-30T13:10:40.007988Z digest=sha256:bfec9309b924eb309f73700514dc2d3af6bdde6beaf0d0c46f923c71aca13843

Observation 9b35be5a-c302-4c6d-ba09-1311eba9a45a · outbound

This paper cites AAMAS , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization AAMAS , pages=

Reference 19

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source=arxiv_source observed=2026-07-30T13:10:40.010607Z digest=sha256:0d514213e6d56bbec24182255b355d7044cf8811fe52fbc5ee1a648680bceae2

Observation e09baa8c-8463-4390-bb34-c1a904ff9c5c · outbound

This paper cites Proceedings of the Nineteenth International Conference on Machine Learning , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the Nineteenth International Conference on Machine Learning , pages=

Reference 20

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Observation ac985c28-2c9e-42de-be3f-0267542167a2 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in neural information processing systems , volume=

Reference 21

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source=arxiv_source observed=2026-07-30T13:10:40.014834Z digest=sha256:182d2ee341e15cad2b5d19f5242fd2a852b67d0c5479d7e7944d749676a9c35c

Observation 581f22e7-d4f0-4c06-81e9-eeaeb1a5aafb · outbound

This paper cites AAMAS , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization AAMAS , pages=

Reference 23

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source=arxiv_source observed=2026-07-30T13:10:40.019464Z digest=sha256:b17ffaeb533b21a8756e5a98761c21ac4b52b0f86a98af3999ef7442f42f8336

Observation 84d68d6e-2611-446a-8835-2f6f625051ce · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 25

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Observation 84943da8-6c04-4960-a849-548c3ef53b05 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the 41st International Conference on Machine Learning , pages=

Reference 26

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source=arxiv_source observed=2026-07-30T13:10:40.026996Z digest=sha256:40c77b2e84e924d22a2ffed1b258db72cfb9aaba7b660a0f61cb80782a18f917

Observation a6546c3c-d624-4042-b8ae-838f64b0c615 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization The Thirteenth International Conference on Learning Representations , year=

Reference 27

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Observation b1896239-d545-4e64-ae5b-b9b602fd09df · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization The Twelfth International Conference on Learning Representations , year=

Reference 31

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source=arxiv_source observed=2026-07-30T13:10:40.042046Z digest=sha256:2eec2b6d97d7bfba283b34e95deb07a50a8a17a97cff7146dc33e75a544de960

Observation ed37beb9-f19b-4353-ac05-1e2813358e7a · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 32

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source=arxiv_source observed=2026-07-30T13:10:40.045272Z digest=sha256:8ae4dab6a18691ca4f55de2fa7965c68a1c2c3fc7ccb224bc3a2b4bd4b58e4bc

Observation 1bbfbf62-031f-4cf0-87d0-053b953ca989 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 33

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Observation 6f8432f8-1a7b-4432-b939-2524777c1750 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 34

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source=arxiv_source observed=2026-07-30T13:10:40.050995Z digest=sha256:89b05b7d4aeaf17c1f6d4d593cfd15c0b8b43a512c8d2dd192d809cf11ba777f

Observation 1767bd78-c183-420f-b3c9-ea7fa08a9f2c · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization The Fourteenth International Conference on Learning Representations , year=

Reference 35

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source=arxiv_source observed=2026-07-30T13:10:40.053283Z digest=sha256:40bffe4b6328b74e84b619c6aa39237b43df6dfc55cdf36ac3cf4eebf9755d13

Observation b794aa82-63aa-46fb-8853-e5f745535011 · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Forty-second International Conference on Machine Learning , year=

Reference 36

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Observation a0c356ec-2aad-4122-994a-84f3e7ede4cd · outbound

This paper cites German Conference on Artificial Intelligence (K.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization German Conference on Artificial Intelligence (K

Reference 37

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Observation 22ff2771-0332-484d-ab35-933a2c64ba0f · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in Neural Information Processing Systems , volume=

Reference 38

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Observation c32f9cce-39ef-444a-a4e1-59079345feaa · outbound

This paper cites Science Advances , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Science Advances , volume=

Reference 41

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Observation fa399056-bb10-47f0-9b9d-c247bf11b63a · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 42

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source=arxiv_source observed=2026-07-30T13:10:40.072956Z digest=sha256:5b9647b2721c44925ce190b04e7a137dd60e4128a91f11b7cd077e84f36b01da

Observation e2efee01-9028-4495-9ab3-d319f69ad31e · outbound

This paper cites Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems , pages=

Reference 43

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source=arxiv_source observed=2026-07-30T13:10:40.075499Z digest=sha256:e42819e48a5e0ad8b83814d162ffdf88f026d9409c434848c61f63e831075b17

Observation 34b2b928-e200-454e-a38f-9f893d17a2ab · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in neural information processing systems , volume=

Reference 44

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Observation 09ebc806-9693-4be4-bb0d-067bde842f70 · outbound

This paper cites Advances in Neural Information Processing Systems 31 (NeurIPS 2018) , pages=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Advances in Neural Information Processing Systems 31 (NeurIPS 2018) , pages=

Reference 45

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source=arxiv_source observed=2026-07-30T13:10:40.080589Z digest=sha256:0eb6bd1831432dfff6b83902945ff9b83a35cda623810fd1b33d0f485f2d7299

Observation aa4dd05f-afc5-491f-9375-89a12fba3460 · outbound

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

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 46

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source=arxiv_source observed=2026-07-30T13:10:40.084048Z digest=sha256:37e642fe3b076b5650a6a5e0d7b07b36cab0f03b1d8756c5e326ba2e0d54ca5b

Observation b54a2df6-e064-4218-beba-5cbbccc6f7d6 · outbound

This paper cites Proceedings of the 35th International Conference on Machine Learning , series=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Proceedings of the 35th International Conference on Machine Learning , series=

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source=arxiv_source observed=2026-07-30T13:10:40.086678Z digest=sha256:4782c75fa8f985e5406b29f83c42eaf068002b5fceac77f5e727b0163b01e70a

Observation c01ef267-7d4e-4a3b-9cd1-8a6f494f1622 · outbound

This paper cites Journal of Machine Learning Research , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Journal of Machine Learning Research , volume=

Reference 48

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source=arxiv_source observed=2026-07-30T13:10:40.090055Z digest=sha256:13690d507739227fd11ee20684fb901072da73de0b13c52f2bc5a4d886767696

Observation c84fa65c-93b0-43ef-b275-1e386d47bafb · outbound

This paper cites Journal of Machine Learning Research , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Journal of Machine Learning Research , volume=

Reference 49

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source=arxiv_source observed=2026-07-30T13:10:40.093447Z digest=sha256:d5011110df80a0aceec42e5a2062ce8fd5a898fe46311deb25a1fd44315741d4

Observation bf17c299-704a-431e-890b-b6d334efa2d0 · outbound

This paper cites Artificial Intelligence , volume=.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Artificial Intelligence , volume=

Reference 50

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source=arxiv_source observed=2026-07-30T13:10:40.116279Z digest=sha256:1910083134281a2615618b8f83d0e080b5b72aec61b75e3543601ed79771f02b

Observation 3b5e5ee5-43a8-43d1-8957-3d15866ff77c · outbound

This paper cites Quasi-monte carlo feature maps for shift-invariant kernels.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Quasi-monte carlo feature maps for shift-invariant kernels

Reference 52

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source=arxiv_source observed=2026-07-30T13:10:40.204747Z digest=sha256:a01d7da8d4ba7a89457307425254517bb218c2e50596d5cf53a88f074322c7d3

Observation 0537b539-2616-4c34-bd44-0c9f7bd0fe4d · outbound

This paper cites Solving Pasur Using GPU-Accelerated Counterfactual Regret Minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Solving Pasur Using GPU-Accelerated Counterfactual Regret Minimization

Reference 53

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source=arxiv_source observed=2026-07-30T13:10:40.261307Z digest=sha256:6c2439ae17bc69d3203cc6eba8dc00a5543f929bc8deb46cacb72fa0a1ca1450

Observation f80c86a7-eb34-4a18-92a0-39ede7190fc3 · outbound

This paper cites u rnkranz, and Martin M \.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization u rnkranz, and Martin M \

Reference 54

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source=arxiv_source observed=2026-07-30T13:10:40.286246Z digest=sha256:d486be6fb425ee85229e8f75b6c115f245b3572cb8c51629843700c5870fd5cd

Observation 9d87f8cc-6a51-4737-96e6-e250d543b3d0 · outbound

This paper cites Superhuman ai for heads-up no-limit poker: Libratus beats top professionals.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Superhuman ai for heads-up no-limit poker: Libratus beats top professionals

Reference 55

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source=arxiv_source observed=2026-07-30T13:10:40.289125Z digest=sha256:855712af4ae416d535379d69eff62b850056dc4cbea24bfeb792158eaafcc4e7

Observation b0128456-5a45-4e84-baaa-9f6c2fe99f2d · outbound

This paper cites Solving imperfect-information games via discounted regret minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Solving imperfect-information games via discounted regret minimization

Reference 56

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source=arxiv_source observed=2026-07-30T13:10:40.291319Z digest=sha256:f9bc6359cd1c9e1cfd9b6f9bda0747f47c948c9fecbd4d01fd295c18c44ccba5

Observation ce3e1d31-165e-400d-8f4d-1cac0323d326 · outbound

This paper cites Superhuman ai for multiplayer poker.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Superhuman ai for multiplayer poker

Reference 57

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source=arxiv_source observed=2026-07-30T13:10:40.294122Z digest=sha256:44364e17a84beaab784fd495ca023b5d2071c9c0b6046ba10ed492082d6dfe1c

Observation 5043b0d0-8c13-4652-8d73-ca172d64c024 · outbound

This paper cites Deep counterfactual regret minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Deep counterfactual regret minimization

Reference 58

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source=arxiv_source observed=2026-07-30T13:10:40.297115Z digest=sha256:01695a9ca1a31000f285eb5f5c063125741eb5d9d11e26cdebc21c3f35244fcd

Observation 29e386f7-843a-4989-a272-63571a696ed0 · outbound

This paper cites Combining deep reinforcement learning and search for imperfect-information games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Combining deep reinforcement learning and search for imperfect-information games

Reference 59

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source=arxiv_source observed=2026-07-30T13:10:40.299286Z digest=sha256:2c1f69f9156489930b0769ee133de108878e461d8a9c7e92bc6d6d337be1912e

Observation 52b22a61-26d6-40b9-84bc-77c6786e8604 · outbound

This paper cites Quasi-monte carlo variational inference.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Quasi-monte carlo variational inference

Reference 60

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source=arxiv_source observed=2026-07-30T13:10:40.302017Z digest=sha256:c3b1162f7a63582582185080fdb3fa7059ec5192a480d00e4144b0d0865e62c6

Observation e56f7a75-75b2-4a18-83c0-98409884cbae · outbound

This paper cites Efficient monte carlo counterfactual regret minimization in games with many player actions.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Efficient monte carlo counterfactual regret minimization in games with many player actions

Reference 61

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source=arxiv_source observed=2026-07-30T13:10:40.304254Z digest=sha256:6a931e853da8e183829d75efc9d4f90c3b03936d3f2955bc463e4bb72d29e46d

Observation 996299ca-2c74-4f9d-b7ed-190bfdd4169e · outbound

This paper cites Randomization of number theoretic methods for multiple integration.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Randomization of number theoretic methods for multiple integration

Reference 62

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source=arxiv_source observed=2026-07-30T13:10:40.307025Z digest=sha256:9f272c6d46ff10c3b950378246690845e34c9347c8aa37118197a7411588abdc

Observation 3ae9d29e-caa3-4eff-bca4-8a9ddff8c841 · outbound

This paper cites Low-variance and zero-variance baselines for extensive-form games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Low-variance and zero-variance baselines for extensive-form games

Reference 63

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source=arxiv_source observed=2026-07-30T13:10:40.309574Z digest=sha256:6165a71c5025d143b02ed6777ddaca4d776ed8835fec0c3743f179668e1d575f

Observation 1ffd36dd-8313-40cf-8d12-5b44f0489355 · outbound

This paper cites Stochastic regret minimization in extensive-form games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Stochastic regret minimization in extensive-form games

Reference 64

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source=arxiv_source observed=2026-07-30T13:10:40.312012Z digest=sha256:572f0b8e36052ac65adc9907f484cae5fd8c5187fdab8853578cc03f93820346

Observation ee785b2e-719f-4055-add6-71312994753c · outbound

This paper cites Faster game solving via predictive blackwell approachability: Connecting regret matching and mirror descent.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Faster game solving via predictive blackwell approachability: Connecting regret matching and mirror descent

Reference 65

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source=arxiv_source observed=2026-07-30T13:10:40.314158Z digest=sha256:a64d73b3c099e0b78bcb27bc5257b8012daf74d4175228e01dc466f106e24b2c

Observation fd488f78-f200-4974-861f-8cef588ea62a · outbound

This paper cites Generalized sampling and variance in counterfactual regret minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Generalized sampling and variance in counterfactual regret minimization

Reference 66

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source=arxiv_source observed=2026-07-30T13:10:40.317118Z digest=sha256:a22518730d47ef128f373d7f570df5d7de657b9cd33824c375076062dad01b03

Observation 4d3a8042-ae7b-4403-a718-914cc3ab2e45 · outbound

This paper cites On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals

Reference 67

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source=arxiv_source observed=2026-07-30T13:10:40.319427Z digest=sha256:891dc661266290162eaed045e9db5552c9c8b2a1de582ac2d4d6b4c6ca568718

Observation 62bfa504-5c4f-4931-8cea-20d627bf694f · outbound

This paper cites Efficient nash equilibrium approximation through monte carlo counterfactual regret minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Efficient nash equilibrium approximation through monte carlo counterfactual regret minimization

Reference 68

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source=arxiv_source observed=2026-07-30T13:10:40.321816Z digest=sha256:ccead27739fdd7c0f256f54fe262e9b07b9782c1b732affcc24fa3542fcd70c6

Observation d8b035c8-e2a2-4bd7-abee-5d7f124427b2 · outbound

This paper cites Rethinking formal models of partially observable multiagent decision making.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Rethinking formal models of partially observable multiagent decision making

Reference 69

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source=arxiv_source observed=2026-07-30T13:10:40.324599Z digest=sha256:2fbc6cea6877a31a674b6e395a327442ecc8a848262380d387524813df911070

Observation a7768613-87ff-49dc-98c3-fefbe5e1d759 · outbound

This paper cites Monte carlo sampling for regret minimization in extensive games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Monte carlo sampling for regret minimization in extensive games

Reference 70

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source=arxiv_source observed=2026-07-30T13:10:40.327053Z digest=sha256:61d103658cf3d20f06a07724f95d7f141e9e56cf8166d22ee2fdc2436fd11584

Observation ea61444e-67ad-4860-9749-ce588928551d · outbound

This paper cites Efficient online pruning and abstraction for imperfect information extensive-form games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Efficient online pruning and abstraction for imperfect information extensive-form games

Reference 71

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source=arxiv_source observed=2026-07-30T13:10:40.329780Z digest=sha256:ba1e70f641c15c27a1beb7e5ac791f117e5a081b6a605c3ed6c1cc6b84706b7e

Observation f9afca4b-aab2-4d93-86b5-125e8efc754c · outbound

This paper cites Effective, Efficient, and General Information Abstraction for Imperfect-Information Extensive-Form Games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Effective, Efficient, and General Information Abstraction for Imperfect-Information Extensive-Form Games

Reference 72

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source=arxiv_source observed=2026-07-30T13:10:40.333080Z digest=sha256:c9ea377e05d8e1b92fb4a44dbbe403748046fd02336766d5e4f7c1e7c7e27bd4

Observation 3d8d9283-c9ce-4c11-8395-59ff403a7e6c · outbound

This paper cites Real-Time Parallel Counterfactual Regret Minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Real-Time Parallel Counterfactual Regret Minimization

Reference 73

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source=arxiv_source observed=2026-07-30T13:10:40.335749Z digest=sha256:eb029c75cba55a9319ef3fba54844662bbcc623eb7d3a674b826d0b8381545a4

Observation f029871a-f3f5-41d4-9aed-c00248800cec · outbound

This paper cites Rl-cfr: improving action abstraction for imperfect information extensive-form games with reinforcement learning.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Rl-cfr: improving action abstraction for imperfect information extensive-form games with reinforcement learning

Reference 74

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source=arxiv_source observed=2026-07-30T13:10:40.339094Z digest=sha256:1d590a31e48bdc2a63246a59fae22b5a6ad234dedbdcc2ba8182e6361627baaf

Observation 2bbc3dd3-1fe6-4a3c-b05f-87f3aa5d961a · outbound

This paper cites PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers

Reference 75

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source=arxiv_source observed=2026-07-30T13:10:40.341741Z digest=sha256:64425d8748685d109583255d113df664a86b62e968f380369b1a034374f279b3

Observation 234832c0-b659-48dc-8a32-5be220ff9470 · outbound

This paper cites Online monte carlo counterfactual regret minimization for search in imperfect information games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Online monte carlo counterfactual regret minimization for search in imperfect information games

Reference 76

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source=arxiv_source observed=2026-07-30T13:10:40.344194Z digest=sha256:dc94e3cafde8ac48101b6271c985d0af4735bd8a768e83b175ee36b7a2384dc5

Observation 4ecb89e7-369b-4377-8dce-d3839162177d · outbound

This paper cites On the theory of systematic sampling, i.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization On the theory of systematic sampling, i

Reference 77

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source=arxiv_source observed=2026-07-30T13:10:40.346672Z digest=sha256:6d2052b15e980202166e011385faab093b34243cf38b5ee1504b28b1f6aba1c0

Observation e1032c3e-c8cd-4620-b647-1f7ea93ea945 · outbound

This paper cites Simple random search of static linear policies is competitive for reinforcement learning.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Simple random search of static linear policies is competitive for reinforcement learning

Reference 78

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source=arxiv_source observed=2026-07-30T13:10:40.349128Z digest=sha256:fda46dd3a36617e1e2a356c99dbd89a4e0a61f5f2965d71215f98dc440271339

Observation 4d93c4a4-2edd-43d7-b03a-f9fd13ccaee2 · outbound

This paper cites Escher: Eschewing importance sampling in games by computing a history value function to estimate regret.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Escher: Eschewing importance sampling in games by computing a history value function to estimate regret

Reference 79

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source=arxiv_source observed=2026-07-30T13:10:40.351732Z digest=sha256:164cb05ae37879b3253dfcc3c15ac488bc5f069c89414751a2f5bca262ad0b9c

Observation 00915647-6405-41ca-a873-78b368e52265 · outbound

This paper cites Reducing variance of stochastic optimization for approximating nash equilibria in normal-form games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Reducing variance of stochastic optimization for approximating nash equilibria in normal-form games

Reference 80

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source=arxiv_source observed=2026-07-30T13:10:40.354462Z digest=sha256:4f508892c63bb26df964b2ce8b7ec616b55c5069a5e1dcab888200b2d21ed2b4

Observation 0dcc18a6-2f84-4dc7-a1da-76aec25bb20c · outbound

This paper cites Faster game solving via asymmetry of step sizes.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Faster game solving via asymmetry of step sizes

Reference 81

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source=arxiv_source observed=2026-07-30T13:10:40.357809Z digest=sha256:96f6cf69c1d0e6098cef015fc220554f0570236adb416f9b40c1f64f4604cd1c

Observation ec20300f-0bad-4cbc-8785-f2a294009941 · outbound

This paper cites A faster parameter-free regret matching algorithm.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization A faster parameter-free regret matching algorithm

Reference 82

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source=arxiv_source observed=2026-07-30T13:10:40.360881Z digest=sha256:ebc96e28c2427ed1390c68120ad4d42d02665f5a11eebb5fba62d5dbfaeeb28e

Observation 79d0a6bb-99f9-46ab-a08e-913b1abfff4c · outbound

This paper cites Monte carlo gradient estimation in machine learning.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Monte carlo gradient estimation in machine learning

Reference 83

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source=arxiv_source observed=2026-07-30T13:10:40.363150Z digest=sha256:cf8fe3e966f62df602011d19dd4015fddddd37cb5e6d274e030a8036d6e281d3

Observation dd042931-689f-4f1b-8100-56d253289dfe · outbound

This paper cites DeepStack : Expert-level artificial intelligence in heads-up no-limit poker.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization DeepStack : Expert-level artificial intelligence in heads-up no-limit poker

Reference 84

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source=arxiv_source observed=2026-07-30T13:10:40.366809Z digest=sha256:b00abfe018cdce930025e5a9872ba89afa253c489dd18ba28a502974b7eb3b62

Observation 8b571367-0696-4a38-a996-8bd1980c6c1e · outbound

This paper cites Random number generation and quasi-Monte Carlo methods.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Random number generation and quasi-Monte Carlo methods

Reference 85

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source=arxiv_source observed=2026-07-30T13:10:40.369974Z digest=sha256:fc0fb7bbf911982894b2facf0d48dfb278aeab0f1baf41ad0c6326bd895f532f

Observation 7fa1b875-84f9-4e0c-8d0f-ec7ab5e8e8da · outbound

This paper cites Monte carlo variance of scrambled net quadrature.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Monte carlo variance of scrambled net quadrature

Reference 86

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source=arxiv_source observed=2026-07-30T13:10:40.372203Z digest=sha256:50086693cf64af7e6441e009d7b7546b99574b82e17e6835715761c1e64dfd33

Observation 3622b025-bd4a-442b-a75f-5a38251ca857 · outbound

This paper cites Learning from scarce experience.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Learning from scarce experience

Reference 87

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source=arxiv_source observed=2026-07-30T13:10:40.374436Z digest=sha256:1f97724f4e5822f85536d8f659415f3c0c09e03a6241e365dbebc56627fd2b0e

Observation a786fa0f-073a-48f1-a02d-a9ff65d854e8 · outbound

This paper cites Accelerating nash equilibrium convergence in monte carlo settings through counterfactual value based fictitious play.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Accelerating nash equilibrium convergence in monte carlo settings through counterfactual value based fictitious play

Reference 88

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source=arxiv_source observed=2026-07-30T13:10:40.377222Z digest=sha256:c5a9e5a8101a3bb72df6b2872ccf09b97bd455256e12fa89eee0425a4aee436d

Observation 8116338d-c3b1-44ab-a4ed-b1d298090161 · outbound

This paper cites Variance reduction in monte carlo counterfactual regret minimization (vr-mccfr) for extensive form games using baselines.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Variance reduction in monte carlo counterfactual regret minimization (vr-mccfr) for extensive form games using baselines

Reference 89

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source=arxiv_source observed=2026-07-30T13:10:40.380040Z digest=sha256:c633d888db7fcfacf6ea0420a65e28ce57940a5514a42d4217649cb824a97f1d

Observation 4f994b21-9bf5-4846-ab5d-514c6d39876e · outbound

This paper cites Student of games: A unified learning algorithm for both perfect and imperfect information games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Student of games: A unified learning algorithm for both perfect and imperfect information games

Reference 90

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source=arxiv_source observed=2026-07-30T13:10:40.383333Z digest=sha256:2f4aef99c75aad30f924558ff219550cbe8afb78648219f57ee3c60939e42fee

Observation d94af9a1-7358-41c5-980c-69e783abd7aa · outbound

This paper cites Distribution of points in a cube and approximate evaluation of integrals.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Distribution of points in a cube and approximate evaluation of integrals

Reference 91

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no resolver link, observed 2026-07-30T13:10:40.385990Z

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source=arxiv_source observed=2026-07-30T13:10:40.385990Z digest=sha256:0aab05f393734f203d9aec029d377b3058e77c08b7cbf38ac9f1b5f3e4dafdd6

Observation 0c573f7b-9f2f-4cef-a678-4106ea3717b9 · outbound

This paper cites Actor-critic policy optimization in partially observable multiagent environments.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Actor-critic policy optimization in partially observable multiagent environments

Reference 92

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no resolver link, observed 2026-07-30T13:10:40.388926Z

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source=arxiv_source observed=2026-07-30T13:10:40.388926Z digest=sha256:b2768e1b5f97b97c2791a8567215ae513321f1e82ddef1bbfcb07018503084b5

Observation be6e0349-e3b3-4541-ada6-d87c88483f77 · outbound

This paper cites DREAM: Deep Regret minimization with Advantage baselines and Model-free learning.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization DREAM: Deep Regret minimization with Advantage baselines and Model-free learning

Reference 93

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no resolver link, observed 2026-07-30T13:10:40.392185Z

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source=arxiv_source observed=2026-07-30T13:10:40.392185Z digest=sha256:9c9b0c5bbd792e19081813bb97699bdcd54c031f625994a62908cc49be6cd5b4

Observation 48ee5349-46e4-4cf5-ace7-4ec3256b71b7 · outbound

This paper cites Monte carlo continual resolving for online strategy computation in imperfect information games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Monte carlo continual resolving for online strategy computation in imperfect information games

Reference 94

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no resolver link, observed 2026-07-30T13:10:40.394435Z

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source=arxiv_source observed=2026-07-30T13:10:40.394435Z digest=sha256:82b0c91197414c4a0636e9277e3498af0b2161855f63f10a4680dde05973149c

Observation 2d1d2969-fd0c-449e-ad48-a784b918e121 · outbound

This paper cites Sound Algorithms in Imperfect Information Games.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Sound Algorithms in Imperfect Information Games

Reference 95

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no resolver link, observed 2026-07-30T13:10:40.397181Z

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source=arxiv_source observed=2026-07-30T13:10:40.397181Z digest=sha256:004d44a9c0b60a7dc5fdad3a054d4656cc4b4202510e20cc136df38aee272af7

Observation a944d5fe-e4e1-4aea-8c91-9571a82da336 · outbound

This paper cites Meta-Learning in Self-Play Regret Minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Meta-Learning in Self-Play Regret Minimization

Reference 96

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source=arxiv_source observed=2026-07-30T13:10:40.399519Z digest=sha256:5aaa44166a25037dcfb7664936542753867ca18ad4ddff39d73f1370b016a123

Observation efd38dac-cf4a-4a96-996d-68738b2af8f8 · outbound

This paper cites Solving Large Imperfect Information Games Using CFR+.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Solving Large Imperfect Information Games Using CFR+

Reference 97

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source=arxiv_source observed=2026-07-30T13:10:40.402079Z digest=sha256:1c31603d5095eae8beafad339812f867e0d6c80833d93bf01002282764b5c6fd

Observation 1b45d45f-eb62-4f35-91fe-48f95cbfb9c4 · outbound

This paper cites Solving games with functional regret estimation.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Solving games with functional regret estimation

Reference 98

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-30T13:10:40.404847Z digest=sha256:909d5fe507e3671cb95f5445fd705b894abec0dcd68550f5c6c8a6b672fcffbd

Observation b96bb10f-9177-44ed-a732-bccafa747f24 · outbound

This paper cites Dynamic discounted counterfactual regret minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Dynamic discounted counterfactual regret minimization

Reference 99

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source=arxiv_source observed=2026-07-30T13:10:40.407883Z digest=sha256:b4d0aec112e2021ca71bc39fa9f3807985a6cca9df717338dfa5d93af8292240

Observation aa3f784a-2243-4a5e-9850-7966cacc8a0c · outbound

This paper cites Deep (predictive) discounted counterfactual regret minimization.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Deep (predictive) discounted counterfactual regret minimization

Reference 100

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source=arxiv_source observed=2026-07-30T13:10:40.410204Z digest=sha256:de2ebe91d5027d43facb5c04daa50652bbae069af66335b7e16183754fe58257

Observation c6fd9235-8bf4-4137-b001-16068fa16245 · outbound

This paper cites Faster game solving via hyperparameter schedules.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Faster game solving via hyperparameter schedules

Reference 101

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source=arxiv_source observed=2026-07-30T13:10:40.413280Z digest=sha256:e93e9f011298efb2c31fe696f990e07efed6f1328abd72b2a93057d5add0dbf7

Observation 1adbb9a6-0f2e-49ef-b20a-d142d2a516eb · outbound

This paper cites Regret minimization in games with incomplete information.

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization Regret minimization in games with incomplete information

Reference 102

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source=arxiv_source observed=2026-07-30T13:10:40.415459Z digest=sha256:96a3a1531c4d05e6f59e0c82abfe6beb181d321c06e2484886dd7032b1d3f4ca

Pith citing papers

Observation e04489e2-452a-430d-8bd1-fe7c8c8668dd · inbound

Agents That Certify Their Own Exploits: Confidence-Scheduled Restricted Responses for Safe Opponent Exploitation cites this paper.

Agents That Certify Their Own Exploits: Confidence-Scheduled Restricted Responses for Safe Opponent Exploitation Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization

Reference 90

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no resolver link, observed 2026-07-31T04:48:47.409963Z

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source=arxiv_source observed=2026-07-31T04:48:47.409963Z digest=sha256:a1504349199e8c2a60f67970bdc88040037aef8123261350ba7d59c59191273a

Observation 3fa5cc88-6f28-497c-8be2-8d8eef14557e · inbound

AV-AIVAT: 74x Cheaper Agent Evaluation with Certified Anytime-Valid Stopping in Imperfect-Information Games cites this paper.

AV-AIVAT: 74x Cheaper Agent Evaluation with Certified Anytime-Valid Stopping in Imperfect-Information Games Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization

Reference 37

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verified exact
local_arxiv, observed 2026-08-07T04:22:29.079025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T04:22:28.902430Z digest=sha256:d978d15680d1566548dd8ffb973fd5899e816e0842b2e4a9e9f6d4412f53902c

Observation 7cdb1697-16a4-4ed5-92fd-fa8fa0b16af2 · inbound

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs cites this paper.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization

Reference 30

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source=pdf_text observed=2026-08-11T14:42:08.768689Z digest=sha256:809d581b0b1d9a49a2073e804daf0a502de0c917e86a71b933de30ef4c404d77