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Paper Citation Record · LEDGER

Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization

As of 7 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 2 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 96 of 96 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:22:28.902430Z

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

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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=sha256:2ad687ed60dfa98cc8499df3d8a806174f848cbf629baa8f07ee62fa5dcf24d7

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=sha256:49288eb0e2eec6824a02e6ea2e1ac094b9a77227fc72a854c1209aa4807177c6

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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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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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=sha256:564cb3199040f66b8891cb8cc139d6fa74d1837d4c4d07847f4075df3f423913

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

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

Reference 35

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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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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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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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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=sha256:49249f1b76a56293ed4d8fb1958d00dacc637c32526ab6ddfed99fe482ef8494

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:c82f10dbaa87e6ee2cc4af46c2bbf5c825f7114f0f9b498e8c7551e1256079ff

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:adb278397cb99f902b9625815cfadcf634dd2d0132b6f2f9f85389fa468e7a34

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=sha256:3aa8b49b5fe216b3d627241d6f68311aee74a660896d4ed8ceaffca7fa9d7412

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:fc108abde8203b8eaa2732b0866cfc57ede6e2dbc48687c62ba8c859855575a5

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=sha256:79ce0b4b553e76b42dfc92cebf83489edfbcebdd8e8110fb65586e297d50d639

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=sha256:6b5ae217fc4bf576b8a7a448c15eb6200679a826ddce5c3cc0ca5d91d6ece2cc

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=sha256:923c5076800d68b2ed5547e157aeefe30d98c5d9600915d58104d39f0910d469

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=sha256:5d3c1265e53eba15d05b9754c7d9b2aed2bb1227283a413b17d567e404f436bc

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:d3cb49e2144658cec523893cebca16a0edb3e217f9c8fbacd29b4da0e67bf7ec

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=sha256:034fca52f27c86257e4bbce06c4f50cb24514fcf928e77050e091415e476167d

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=sha256:91727788c82ae42c43c5d28e2dcf0ad299ed14634f40bacc8f8fbc44d29c4b1c

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:d634925f22b25c904816384a23f11d38a683696e0d153346adb90b8988b65c54

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=sha256:1ed387e07625d66ae6823c72e4812737c644b74232b77ca4c36cd2db573f3d4a

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:f9ee05b2edd23904b6bf09734b78044c2389faf8979f881ea23db73f70a2c89c

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=sha256:5b07e7feb50de9e8a4b761b9924eaa1ab4f692afcd413d6b2abb2d7c2717316d

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=sha256:2e353dc41e8e08a666d0108eb2e969832afb3d569a661f971aa415340b55e0f0

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=sha256:76859771c796a55a6bcb63387ce2c0cc246c9c310ff8a82667b1e84d307aa0e9

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=sha256:906d1fc60acfcabac93720bf5bc11f08206ea7a37e41d10de36efbbe9a9ca725

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=sha256:8c6f3ffeecf78fb03d7d4e642c3b32ca8aa16444ace0c98eb34b6e8d9ede1efd

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:d5cc139eae53cfdfe8141e342139f0f550ea0de7c24a3c80b9b87f655ed49940

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:d91ff734206d6a282a04425e6c6b31975b1c7e35af2c3d6802a6f1bcfcc6d68d

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:a86602b55ebe159afcabf7248e6b368d7a62d2bdeac84b5c814bf9c55bbd25cf

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=sha256:2afe1ff1a5e78a00e0532d920ef65f25041190e5fe26a34d00a39e31002c9f00

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=sha256:3ce398a00a52854ec2e1e252115907294798647341a4064e3e4b8fb1627462cd

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:ca47ac50dd2abedba4496976ef1bd58847d50c5139b219db0f4c835a4bacb356

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:d1aa859e400f7fa6ea93cff27aeccae299cb9602bcad54439fb7a7ebdcc8c90f

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=sha256:4cfd251d70bccef31b60b1daf35e4942e1c61cdb4f1a5cf2764a4852ddabad71

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=sha256:6bfc910e5199f82dfefb9f5eb8735e111f1d93d4cb8422693b429f15ebd94a92

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=sha256:202aa4c9ca6e0c7efb9949667c2a4177fb9cc1c06d9d039bf7a38f4edcbed896

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=sha256:6cce8bfe523cbeb07e5a04453d4086fa9d03b82df88ca2cdd28fa6fb7c81a2cf

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=sha256:074cafcfd42d2388866459fe29c77b0f43ffd1a68a9fddc00e0efe6df0092546

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=sha256:4294d60c685b8b8cdd2aac6c9c868e7224e0420170b4c014aa7e061fd3abf963

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:e946fa50bfc5ae6868f85c29ff540a7d9c531b506beb078225b9a9c5fd5edb29

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=sha256:8265cd91b2d9cc1b93d997e7602773ef167d54647e4d6b2a40c0cf45a069e578

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=sha256:5be0ddf9edf53fe92683cda9200e17d8605c03d5210fa14694c735fd714ccbd8

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:b10a09e47eb0490c054c642d6a0127b4771d96cee7c537fd65c766f535038892

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:b8b1f1512960078aa463876e83ef57fff77ac382d265f7085c1fcc098d758108

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=sha256:544c7e8feecf9f6d32202f04559f0fb6684c118edfd95ab8280e2dc98075855c

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=sha256:0b6fb303cff37570ddcd2a843f3bf09d85da35f446c6126934bcc05dd0bf684c

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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no resolver link, observed 2026-07-30T13:10:40.374436Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-30T13:10:40.374436Z digest=sha256:9d1b0bbad6a2db151f0e9b71137bcf3b6b8bb2ef5f0a1c04ec24b4d73cbb7a64

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:f99d63f4346933166e2701032d97465b2b1246713062fa153282bde86ae39e04

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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no resolver link, observed 2026-07-30T13:10:40.380040Z

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source=arxiv_source observed=2026-07-30T13:10:40.380040Z digest=sha256:f132e206a6fe466b8e679acc8789ea327fc97fe4edf4c1d3afc67efcb5221a95

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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no resolver link, observed 2026-07-30T13:10:40.383333Z

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source=arxiv_source observed=2026-07-30T13:10:40.383333Z digest=sha256:a22d1d52bc7d6895a461be29d7059e5eaa4997fb7b744ed8ed1f08d86effecaa

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=sha256:9545ad10a004639013013c784f493c87ecd809c99a351d74c2c5ba2b34c3395d

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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source=arxiv_source observed=2026-07-30T13:10:40.388926Z digest=sha256:eb7274401973cb9eeb4aac5ac8e817b3c438bc4fb05cde33e0fb227fc65f475b

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:a2e6858f5421407be82bf411ee37ff7dd0acf9d6ea896259758e024869698b63

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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source=arxiv_source observed=2026-07-30T13:10:40.394435Z digest=sha256:85c257213a2c904fd879bd05aed5c226888e5cf8a97de865f95e9831dceb3d8e

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=sha256:336b60f0030fa3487899b428064307178781725b3331f6c5569b5ff7bc39f4dd

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=sha256:37ac926c99fa0fafa1d03d6944b3277445a1e8a285c9f63f27470bb5dddc30b8

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:d52bd3de32a3605ea179c900d68d1111d39bf0bfa101cb5729576f425b27595f

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=arxiv_source observed=2026-07-30T13:10:40.404847Z digest=sha256:d70f7ca0ee72d9e2ee0f8f1a80b7c93766be545b3c644ed53abf52d331f6f2cc

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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no resolver link, observed 2026-07-30T13:10:40.407883Z

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source=arxiv_source observed=2026-07-30T13:10:40.407883Z digest=sha256:9e1fdb4b6488f2c58b79651205704ea4f49069c74cd6e21cca24431738b80f24

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=sha256:051589975e577cfcb68db339540f2ddee3de17e57d1fd370f8f00fdc6306e0ff

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=sha256:9f64976993352596a95d3d975dc89d5698ba9359a22499f0b12daeb8488d51c2

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=sha256:99623518c1b03977cace5cc18ed378deb6722046422d1d8b1abdd770f2ee6797

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=sha256:859860b0fe1355bfe6259e09e2c2d622f2aae39c932980cee3942891544e08eb

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

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source=pdf_text observed=2026-08-07T04:22:28.902430Z digest=sha256:4408f1f26d3014fbde3c0c7282dd3652e5e73c6454675e82ac19d58069c77b72