Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making | Paper Citation Record

Observation db279f33-f1da-4de9-bebe-eb88f9adbf2a · outbound

This paper cites Playing repeated games with Large Language Models.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Playing repeated games with Large Language Models

Reference 1

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Gemini: A Family of Highly Capable Multimodal Models

Reference 2

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This paper cites The claude 3 model family: Opus, Sonnet, Haiku.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making The claude 3 model family: Opus, Sonnet, Haiku

Reference 3

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This paper cites Qwen Technical Report.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Qwen Technical Report

Reference 4

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This paper cites Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Reference 5

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This paper cites Training Verifiers to Solve Math Word Problems.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Training Verifiers to Solve Math Word Problems

Reference 6

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This paper cites GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents

Reference 7

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This paper cites DeepSeek-V3 Technical Report.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making DeepSeek-V3 Technical Report

Reference 8

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Observation 2794b4f1-eeb1-45e2-bcbb-2ac90dc8244e · outbound

This paper cites GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Reference 9

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This paper cites Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Can Large Language Models Serve as Rational Players in Game Theory? A Systematic Analysis

Reference 10

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This paper cites The Llama 3 Herd of Models.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making The Llama 3 Herd of Models

Reference 11

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

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Are ChatGPT and GPT-4 Good Poker Players? -- A Pre-Flop Analysis

Reference 12

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Observation 1e557b64-bf58-4d69-8b69-b76e02d04dfa · outbound

This paper cites GameArena: Evaluating LLM Reasoning through Live Computer Games.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making GameArena: Evaluating LLM Reasoning through Live Computer Games

Reference 13

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This paper cites Towards Reasoning in Large Language Models: A Survey.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Towards Reasoning in Large Language Models: A Survey

Reference 14

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This paper cites AvalonBench: Evaluating LLMs Playing the Game of Avalon.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making AvalonBench: Evaluating LLMs Playing the Game of Avalon

Reference 15

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making AgentBench: Evaluating LLMs as Agents

Reference 16

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This paper cites Strategic Behavior of Large Language Models: Game Structure vs. Contextual Framing.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Strategic Behavior of Large Language Models: Game Structure vs. Contextual Framing

Reference 17

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This paper cites Revisiting the Calibration of Modern Neural Networks.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Revisiting the Calibration of Modern Neural Networks

Reference 18

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This paper cites What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models

Reference 19

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This paper cites GPT-4 Technical Report.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making GPT-4 Technical Report

Reference 20

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This paper cites The Effect of Sampling Temperature on Problem Solving in Large Language Models.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making The Effect of Sampling Temperature on Problem Solving in Large Language Models

Reference 21

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making MarioGPT: Open-Ended Text2Level Generation through Large Language Models

Reference 22

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents

Reference 23

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This paper cites Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions

Reference 24

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Voyager: An Open-Ended Embodied Agent with Large Language Models

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This paper cites Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation

Reference 26

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Mistral 7B

Reference 27

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This paper cites Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf

Reference 28

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making On the Frozen F-theory Landscape

Reference 29

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

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This paper cites Evaluating and Enhancing LLMs Agent based on Theory of Mind in Guandan: A Multi-Player Cooperative Game under Imperfect Information.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Evaluating and Enhancing LLMs Agent based on Theory of Mind in Guandan: A Multi-Player Cooperative Game under Imperfect Information

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This paper cites Battle of the Large Language Models: Dolly vs LLaMA vs Vicuna vs Guanaco vs Bard vs ChatGPT -- A Text-to-SQL Parsing Comparison.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Battle of the Large Language Models: Dolly vs LLaMA vs Vicuna vs Guanaco vs Bard vs ChatGPT -- A Text-to-SQL Parsing Comparison

Reference 32

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This paper cites On the volume of convolution bodies in the plane.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making On the volume of convolution bodies in the plane

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:06:49.406776Z

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Observation acafd906-815f-41b2-811b-3f2c8be59549 · outbound

This paper cites LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models

Reference 34

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This paper cites The battlefield consists of 5 rows (corresponding to y-coordinates 0-4).

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making The battlefield consists of 5 rows (corresponding to y-coordinates 0-4)

Reference 35

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This paper cites Human units are placed on the left side of the battlefield, remain stationary, and attack approaching enemies.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Human units are placed on the left side of the battlefield, remain stationary, and attack approaching enemies

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:52.749361Z

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Defending units fire bullets or activate skills to attack enemies

Reference 37

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Observation b81768cf-3b83-482e-834e-8cac2d7e5fcd · outbound

This paper cites Placing a new unit in an occupied cell is not allowed.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Placing a new unit in an occupied cell is not allowed

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:52.435311Z

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Observation 55c7ce57-13bf-45d4-9d1a-8aa5882f8eb7 · outbound

This paper cites If a unit’s health drops to 0, it is eliminated and removed from the battlefield.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making If a unit’s health drops to 0, it is eliminated and removed from the battlefield

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:52.250295Z

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Observation e901168c-15bd-495f-a0e7-09db75830f9c · outbound

This paper cites If any enemy successfully reaches the left side of the battlefield, the player loses.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making If any enemy successfully reaches the left side of the battlefield, the player loses

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:52.050709Z

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This paper cites Gold characters cost three times as much as bronze characters, but their stats (attack, health, numerical skill effects, etc.) are twice as high.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Gold characters cost three times as much as bronze characters, but their stats (attack, health, numerical skill effects, etc.) are twice as high

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:51.861430Z

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Observation 097ae285-a9f8-4c6e-a4c4-a6c8aed27e01 · outbound

This paper cites If both sides have the same number of characters, the invader attacks first.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making If both sides have the same number of characters, the invader attacks first

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:51.690917Z

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Unresolved cited work

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Observation f10f3028-fd45-4d34-b325-c13d4ed087d7 · outbound

This paper cites However, if there are Taunt minions on the opponent’s side, attackers must prioritize attacking them.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making However, if there are Taunt minions on the opponent’s side, attackers must prioritize attacking them

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:51.335745Z

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Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Unresolved cited work

Reference 45

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This paper cites A.2.2 Invader units Unit Attributes FireLizard Attack: 2, Health: 2, Cost: 1, Ability: Deals 2 damage to the enemy that killed it upon death.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making A.2.2 Invader units Unit Attributes FireLizard Attack: 2, Health: 2, Cost: 1, Ability: Deals 2 damage to the enemy that killed it upon death

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.976355Z

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Observation cd290fc0-05d2-44c4-af2d-6b11fef7d50a · outbound

This paper cites Each faction consists of three characters.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Each faction consists of three characters

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.801852Z

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Observation ac745349-2c9c-4fee-8737-614746a7e60c · outbound

This paper cites In each round, the three Invader characters act first in order, followed by the three Defender characters.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making In each round, the three Invader characters act first in order, followed by the three Defender characters

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.622299Z

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Observation 08fd9254-f16e-4de8-8c93-28b74e0e046d · outbound

This paper cites On each turn, a character uses the next skill in their list and continues cycling through them in order.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making On each turn, a character uses the next skill in their list and continues cycling through them in order

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.480265Z

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Observation 9098988c-7836-419b-9817-423b500e47cc · outbound

This paper cites Light and Dark counter each other with 1.5× damage.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making Light and Dark counter each other with 1.5× damage

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.326721Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2af913c9-e727-4979-866a-7697738ec073 · outbound

This paper cites A.3.2 Invader skills 15 Skill Name Description Fire Skills flame_splash Deals 12 damage and applies Burning for 2 rounds (1 layer, 5 damage per round).

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making A.3.2 Invader skills 15 Skill Name Description Fire Skills flame_splash Deals 12 damage and applies Burning for 2 rounds (1 layer, 5 damage per round)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.173728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3781921d-0e50-40bd-b726-d4c3ebb973d1 · outbound

This paper cites B.1 Rule violation Rate (RVR) This metric measures how often a model’s initial strategy proposal fails to adhere to the game’s explicit rules, particularly budget constraints.

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making B.1 Rule violation Rate (RVR) This metric measures how often a model’s initial strategy proposal fails to adhere to the game’s explicit rules, particularly budget constraints

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:06:50.022346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers