arXiv paper examining whether outcome reward optimization produces reliable AI reasoning. The research challenges assumptions that reward signals alone ensure verifiable or causally meaningful decision-making processes.
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Outcome Rewards Do Not Guarantee Verifiable or Causally Important Reasoning
Outcome reward optimization fails to guarantee verifiable reasoning or causal decision-making in AI models, challenging a foundational assumption in reward-based training approaches.
Tuesday, April 28, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
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