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SPOKE

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RESEARCH · 1 SOURCE · arXiv cs.AI

arXiv paper introduces SPOKE to improve strategic play of compact poker agents

The paper (arXiv:2610.27028v1) proposes Strategic Preference Optimization with KL-anchored Equilibrium (SPOKE), which combines teacher-relative value penalties, policy anchoring, risk constraints, and structured rationale supervision to improve strategic play under hidden information. Evaluated against SFT, DPO, GRPO, and GSPO on frozen models (SmallThinker, Qwen3, Gemma-3) and three runs of a SmallThinker-4B-A0.6B policy, SPOKE yielded lower mean exploitability in Kuhn (0.213) and Leduc (1.081) and higher six-max top-1 agreement (0.775) while maintaining teacher KL similar to SFT.

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