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Peisong Wang

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#machine learning Preprint Oct 2026

Process Reward Modeling with Reliability- and Conservatism-Aware Bayesian Belief

BayesianPRM is proposed, which treats the process reward as a random variable within a reward hypothesis space and maintains a Bayesian belief over it, and yields a reliability- and conservatism-aware Bayesian belief, whose expectation determines the process reward.

Zhong-Jian Qiao, Zhi-Xiang Zhou, Jiafei Lyu et al. · 0 citations
Preprint Aug 2026

$R^3$-Bench: LLMs Struggle with Resource-Rational Reasoning under Shared Budgets

$R^3$-Bench is introduced, which evaluates six-problem suites under shared budgets across mathematics, competitive programming, and abstract reasoning in tool-free and agentic settings, and exposes a persistent gap between demonstrated competence and shared-budget realization.

Peisong Wang, Zhiwei Ma, Bo-Wen Liu et al. · 0 citations

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