most citedScalePRM: Training Process Reward Models by Scaling Verification Compute Without Ground Truth

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cs.LG2026

C-MORAL: Controllable Multi-Objective Molecular Optimization with Reinforcement Alignment for LLMs

Rui Gao, Youngseung Jeon, Swastik Roy +2

Large language models (LLMs) show promise for molecular optimization, but aligning them with selective and competing drug-design constraints remains challenging. We propose C-Moral…

cs.LG2025★ 1 cited

ScalePRM: Training Process Reward Models by Scaling Verification Compute Without Ground Truth

Salman Rahman, Sruthi Gorantla, Arpit Gupta +3

Training process reward models (PRMs) requires step-level correctness labels, obtained either through expensive human annotation or by relying on ground-truth answers, limiting the…