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Paper Citation Record · LEDGER

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

As of 14 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2608.09586.

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

pith.paper-citation-record.v1
2608.09586 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:42:08.814379Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

  • verified exact1
  • verified fuzzy22
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 92451f94-8720-4047-b76c-4dac168aeb94 · outbound

This paper cites Using counterfactual regret minimization to create competitive multiplayer poker agents.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Using counterfactual regret minimization to create competitive multiplayer poker agents

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.641861Z digest=sha256:246d6773c52a1564a925824b20356151c4e18e6ac00b5ad4c7fc9d867d0f9400

Observation ebbc12f4-477f-46b5-995b-7af06df0385b · outbound

This paper cites Qwen Technical Report.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-11T14:42:08.646733Z digest=sha256:23278e2fd32dd89bc905a632fe57cff3ecb644c9834671cdcd48a8c136377edd

Observation 8104436c-df10-4d73-b7a3-7071526909c4 · outbound

This paper cites Opponent modeling in poker.Aaai/iaai, 493(499):105, 1998.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Opponent modeling in poker.Aaai/iaai, 493(499):105, 1998

Reference 3

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raw_fallback, observed 2026-08-11T14:42:09.434272Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.651893Z digest=sha256:226b3a0345b71d9266aca80345f0322059d968ceee8d0a5f9e2449a11811c175

Observation db8fa8fc-518c-4c31-b169-ecec9cd05be3 · outbound

This paper cites Heads-up limit hold’em poker is solved.Science, 347(6218):145–149, 2015.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Heads-up limit hold’em poker is solved.Science, 347(6218):145–149, 2015

Reference 4

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raw_fallback, observed 2026-08-11T14:42:09.413296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.656226Z digest=sha256:341e985828bb5a5745eadc522b7472aacfd570a537cd12f1ebf8dcc730ada3f3

Observation 555b44e2-ffb1-4a09-bdea-7213e88d0c0b · outbound

This paper cites an unresolved cited work.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Unresolved cited work

Reference 5

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.660936Z digest=sha256:64ab5feab4b8562bc41ac8cbc2b839342e2feb77b67fb79f5b035020d1e3e4c8

Observation da256e99-6ba0-432b-86dd-b916bff978b6 · outbound

This paper cites Superhuman ai for heads-up no-limit poker: Libratus beats top professionals.Science, 359(6374):418–424, 2018.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Superhuman ai for heads-up no-limit poker: Libratus beats top professionals.Science, 359(6374):418–424, 2018

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T14:42:08.665642Z digest=sha256:6c61f4da86baa480e3e449248e08d52679c7ff16f9cae8e36ba7c7af1bd029ac

Observation b5aea766-2fea-497c-82c2-1b31a2325f2a · outbound

This paper cites Superhuman ai for multiplayer poker.Science, 365(6456): 885–890, 2019.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Superhuman ai for multiplayer poker.Science, 365(6456): 885–890, 2019

Reference 7

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source=pdf_text observed=2026-08-11T14:42:08.670169Z digest=sha256:e13d2e0370f804bc81c4d4e3ffef31362ee6e06614b0309f78d33dc17c5af78e

Observation 445b8e4c-f1e7-4583-85b1-7a58b6e9852d · outbound

This paper cites An investigation into tournament poker strategy using evolutionary algorithms.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs An investigation into tournament poker strategy using evolutionary algorithms

Reference 8

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.674131Z digest=sha256:6de5d758cd0f0e687cac087d118920b7e520babe8934ccb64d6dca9ce3670ae5

Observation 93a48a4f-787f-46eb-aa80-7f606b763fb4 · outbound

This paper cites Gambler’s ruin and the icm.Statistical Science, 37(3): 289–305, 2022.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Gambler’s ruin and the icm.Statistical Science, 37(3): 289–305, 2022

Reference 9

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.678320Z digest=sha256:386a73117b06c2aaa62d9eca9fd28dbe6baf46b222a80643092896c62b4397b6

Observation 61c0df4a-5cfc-4fc7-90ec-02cefcd715a3 · outbound

This paper cites Computing an approximate jam/fold equilibrium for 3-player no-limit texas hold’em tournaments.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Computing an approximate jam/fold equilibrium for 3-player no-limit texas hold’em tournaments

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.682301Z digest=sha256:c7ec385f7fc0bd8b3791c9432bf59e1b7eb9af0357fd932e9d45d8df3ba78840

Observation aeaca768-c12e-47d2-89d2-619b89c68ea4 · outbound

This paper cites Computing equilibria in multiplayer stochastic games of imperfect information.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Computing equilibria in multiplayer stochastic games of imperfect information

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.686463Z digest=sha256:5197d19deae41f08546252478a6c8282f3194fc8d9ff841c4bf59cbd04241865

Observation 9e60d6af-63cc-466a-821e-f0909279577c · outbound

This paper cites Successful nash equilibrium agent for a three-player imperfect-information game.Games, 9(2):33, 2018.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Successful nash equilibrium agent for a three-player imperfect-information game.Games, 9(2):33, 2018

Reference 12

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raw_fallback, observed 2026-08-11T14:42:09.307322Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.690529Z digest=sha256:a502a91dd213c75730f8a0bcbe041b4c3a897f4cf721c9bdbcf546619e829b34

Observation 9de64015-0e0d-4ea4-a833-6221ec7aba8e · outbound

This paper cites Regret minimization in multiplayer extensive games.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Regret minimization in multiplayer extensive games

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.694843Z digest=sha256:c48d78525ac7d84e3e9f3d25f05f1dd8d21c5ca3f968e825be73f11e3f5f6248

Observation b0ecbb25-86f3-4e8e-940d-51c0fe8f59a7 · outbound

This paper cites On strategy stitching in large extensive form multiplayer games.Advances in Neural Information Processing Systems, 24, 2011.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs On strategy stitching in large extensive form multiplayer games.Advances in Neural Information Processing Systems, 24, 2011

Reference 14

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raw_fallback, observed 2026-08-11T14:42:09.279332Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.698909Z digest=sha256:d3c5a42ee84782dd527b5d86fa79c83855f71c94c066bb76369e64ed4e88ca30

Observation 8685ec5a-8c0d-4767-aa7a-219954e41e98 · outbound

This paper cites Lossless abstraction of imperfect information games.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Lossless abstraction of imperfect information games

Reference 15

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raw_fallback, observed 2026-08-11T14:42:09.265811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.702833Z digest=sha256:79d950773ed1487849c506ff7f22d18f73326f07461b5177de5f45b371f361d7

Observation 2a7f78b1-fb7d-49e3-81aa-df599c66c61a · outbound

This paper cites The Llama 3 Herd of Models.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs The Llama 3 Herd of Models

Reference 16

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source=pdf_text observed=2026-08-11T14:42:08.706867Z digest=sha256:61fe5db126ef23e77c38c5d2b916405de2f6eb1b35324e11a9a02fea864e5db7

Observation 645798f7-707f-4981-b613-2984ad42c77f · outbound

This paper cites Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4

Reference 17

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source=pdf_text observed=2026-08-11T14:42:08.711588Z digest=sha256:e4b2acf486fec7e897cf25e1d88a43229ecc4e96011c2d285b21867f802793d8

Observation 06b9a56b-1884-45a3-acc9-bf8b3b424d47 · outbound

This paper cites Are ChatGPT and GPT-4 Good Poker Players? -- A Pre-Flop Analysis.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Are ChatGPT and GPT-4 Good Poker Players? -- A Pre-Flop Analysis

Reference 18

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source=pdf_text observed=2026-08-11T14:42:08.716128Z digest=sha256:d03cf60be007500ce3fae3043897ece079bd179bee6bd71548fdd246417f3a6f

Observation dd72abd1-5894-4dfd-a494-2f1a40e995db · outbound

This paper cites Harville.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Harville

Reference 19

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source=pdf_text observed=2026-08-11T14:42:08.720615Z digest=sha256:99494e9726e68d43364c5e7863eb836dbdc75ef53f9305b0bc5ab1e80f37391a

Observation c1a5dbff-1cab-4848-8ea4-6644c88d9e17 · outbound

This paper cites Effective short-term opponent exploitation in simplified poker.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Effective short-term opponent exploitation in simplified poker

Reference 20

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raw_fallback, observed 2026-08-11T14:42:09.252297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.725316Z digest=sha256:d3401739c718e5cdd0c43f0fa6292246c58abf6342848dd2630097ade86a3b55

Observation f6659a7c-65de-4e93-9fe7-f73860e5310c · outbound

This paper cites PokerGPT: An End-to-End Lightweight Solver for Multi-Player Texas Hold'em via Large Language Model.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs PokerGPT: An End-to-End Lightweight Solver for Multi-Player Texas Hold'em via Large Language Model

Reference 21

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source=pdf_text observed=2026-08-11T14:42:08.729768Z digest=sha256:fa5648294b637be6d76fa8e61d7d8cabcecbc039054b31a3f4e5b4576f19e33c

Observation 3afad752-d7f1-4608-bb94-00396b161d44 · outbound

This paper cites Empirical validation of the independent chip model.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Empirical validation of the independent chip model

Reference 22

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.734067Z digest=sha256:1948fcd47b67c3feadd90767e370254ae51c602f47ad226707aa5c8aa0fdde71

Observation cdd4baf0-9e4f-4dee-af24-0ccb26412840 · outbound

This paper cites Leslie and Edmund J.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Leslie and Edmund J

Reference 23

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doi, observed 2026-08-11T14:42:08.854511Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.738622Z digest=sha256:f081df3682a1b7eb1161ee422e9cad10ecfafb474d1d4ffb6af62efe66e34fab

Observation e10bde8c-8ad5-43b3-b7fa-c454248f4ea8 · outbound

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

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Efficient online pruning and abstraction for imperfect information extensive-form games

Reference 24

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source=pdf_text observed=2026-08-11T14:42:08.742791Z digest=sha256:6bf1b0587ad40b22aec0528b4dc0fe3563a7ff8cf9f441dd78d2601520b24340

Observation 4542a7ca-1ac6-48c5-ab56-9017b9700303 · outbound

This paper cites Agents that certify their own exploits: Confidence-scheduled restricted responses for safe opponent exploitation, 2026.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Agents that certify their own exploits: Confidence-scheduled restricted responses for safe opponent exploitation, 2026

Reference 25

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source=pdf_text observed=2026-08-11T14:42:08.746950Z digest=sha256:07ba979480faa47217634b2a2ffd35ed1ec956ee1dee7ed315ed93f6f3bc07d4

Observation 57c47e4f-f770-4f69-ba25-2880d6b85310 · outbound

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

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Effective, Efficient, and General Information Abstraction for Imperfect-Information Extensive-Form Games

Reference 26

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source=pdf_text observed=2026-08-11T14:42:08.751270Z digest=sha256:e438f876c98b4a74aa46f50b7e69224a7a27544f12651417499d2663ba3066f4

Observation c42c7e8c-aded-4e39-bf01-c6e6d243c804 · outbound

This paper cites Real-Time Parallel Counterfactual Regret Minimization.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Real-Time Parallel Counterfactual Regret Minimization

Reference 27

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no resolver link, observed 2026-08-11T14:42:08.756158Z

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source=pdf_text observed=2026-08-11T14:42:08.756158Z digest=sha256:66cddfa658af4b2a64d19eae6fd97fe620383fab7fb2cafa0b18556d301d1866

Observation 70f2bcfd-f940-443a-a8a6-76e93aaa7d42 · outbound

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

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Rl-cfr: improving action abstraction for imperfect information extensive-form games with reinforcement learning

Reference 28

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no resolver link, observed 2026-08-11T14:42:08.760622Z

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source=pdf_text observed=2026-08-11T14:42:08.760622Z digest=sha256:e7784a0947507c03271f7bdc0bbdf53b17e177177559cfb5423e14c452a34b83

Observation aba6dcf3-39c9-4c9c-9fd4-aff9c475dc31 · outbound

This paper cites Av-aivat: 74x cheaper agent evaluation with certified anytime-valid stopping in imperfect-information games, 2026.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Av-aivat: 74x cheaper agent evaluation with certified anytime-valid stopping in imperfect-information games, 2026

Reference 29

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raw_fallback, observed 2026-08-11T14:42:09.200315Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.764740Z digest=sha256:5d3f14c767f8fb3780340ffa4755c2d31aafa902945beac455edfcd1f33b0a01

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

This paper cites Correlated Chance Sampling for Monte Carlo Counterfactual Regret Minimization.

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:42:08.768689Z digest=sha256:28eed978ed7da73cdfc7b87f392ed3740c79eb0ad79e202f96361aa9ad136cd4

Observation fd10e974-c237-4300-9ee8-3136a9e0382d · outbound

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

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers

Reference 31

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no resolver link, observed 2026-08-11T14:42:08.773037Z

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source=pdf_text observed=2026-08-11T14:42:08.773037Z digest=sha256:a096ebb7eb3da37adb5c8db835695daeb3c732ee8208e3f6e1c5e778fe97b951

Observation f2e5f1f2-6afb-476e-b2a5-973b4d98c88a · outbound

This paper cites Two Plus Two Publishing LLC, 1999.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Two Plus Two Publishing LLC, 1999

Reference 32

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raw_fallback, observed 2026-08-11T14:42:09.184537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.777417Z digest=sha256:54de246d626707243503fbd75c4e0a12c79b1ddf744c4e0b189325f99ddf6675

Observation d68f1aba-f4bc-4f22-a7f8-9142b1ca8054 · outbound

This paper cites A near-optimal strategy for a heads-up no-limit texas hold’em poker tournament.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs A near-optimal strategy for a heads-up no-limit texas hold’em poker tournament

Reference 33

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raw_fallback, observed 2026-08-11T14:42:09.171777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.781251Z digest=sha256:b6476cbf0d2707a19e4816c1f2392c02c0ae576b4ccd9afbddec02bd6f7face2

Observation 81cac631-bea6-4076-bca3-3af04909b1b8 · outbound

This paper cites Deepstack: Expert-level artificial intelligence in heads-up no-limit poker.Science, 356(6337):508–513, 2017.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Deepstack: Expert-level artificial intelligence in heads-up no-limit poker.Science, 356(6337):508–513, 2017

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:42:08.785054Z digest=sha256:0fc44dd5d4525cacf1a86143d330ca76cbc8a1306eacb1df5aa7838b255feb38

Observation b1fc7824-d886-4c6e-8150-769417c45d5c · outbound

This paper cites The state of solving large incomplete-information games, and application to poker.Ai Magazine, 31(4):13–32, 2010.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs The state of solving large incomplete-information games, and application to poker.Ai Magazine, 31(4):13–32, 2010

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:42:09.152299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.789057Z digest=sha256:16e22c82397d21e2a264c74f4aa753e6b90ba5857579a77754527f3947522874

Observation 531aebf8-e7f0-491d-b50b-9c39ea2e2db7 · outbound

This paper cites an unresolved cited work.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-11T14:42:09.139908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.792983Z digest=sha256:69f07ad5c3a7ba889ace913952d1b7331a24242ee870a8c81397075c3a905d95

Observation 0edc583e-2236-426e-86c1-e36c3253d764 · outbound

This paper cites Two Plus Two Publishing LLC, 2007.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Two Plus Two Publishing LLC, 2007

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:42:09.126188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.797344Z digest=sha256:07b7d2d66574ce5b21ee37251dce2cbc87df12e79e06a6552d2d34a84589d48c

Observation d3c8c3aa-3d8e-463e-ac21-8eff0a7a6dba · outbound

This paper cites Two Plus Two Publishing, 1994.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Two Plus Two Publishing, 1994

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:42:09.109300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.801295Z digest=sha256:78e2691fc9ccb8a58bc11f5e62982ac22ce47147caf5f7c403223a739e000a7f

Observation 24b5d762-86ed-44a1-a2e8-5c81d334a12e · outbound

This paper cites Bayes’ bluff: opponent modelling in poker.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Bayes’ bluff: opponent modelling in poker

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:42:09.095944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.805362Z digest=sha256:438911b0486969a5375cf6185cbe91a6d628c90b53a591e3abeea9f643a45543

Observation aa73b4b3-76ff-4e1e-9ceb-775f6449f4b5 · outbound

This paper cites A parameterized family of equilibrium profiles for three-player kuhn poker.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs A parameterized family of equilibrium profiles for three-player kuhn poker

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:42:09.082832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.809304Z digest=sha256:186c4faf2d13c72878b7bee4c758e40c80883f5d932a9a38068bb1b02aa4b937

Observation a684ce09-e746-4da9-b4d5-c5973ba33fa7 · outbound

This paper cites Regret mini- mization in games with incomplete information.Advances in neural information processing systems, 20, 2007.

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs Regret mini- mization in games with incomplete information.Advances in neural information processing systems, 20, 2007

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:42:09.070349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T14:42:08.814379Z digest=sha256:ea6f6391ce72d18cad193cadf4a18694e9c8a6a78ad012afb32a99324fe567c3

Pith citing papers

No inbound Pith citation observations are available.