arxiv
PublishedJuly 27, 2026 at 4:00 AM
—neutral
Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning
Publisher summary· verbatim
arXiv:2507.01551v3 Announce Type: replace-cross Abstract: Process Reinforcement Learning~(PRL) has demonstrated considerable potential in enhancing the reasoning capabilities of Large Language Models~(LLMs). However, introducing additional process reward models incurs substantial computational overh
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivA Consensus-Based Framework for Relative Preference Evaluation of Large Language Models7harxivProbing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders7harxivData Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA7harxivEnjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging7hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗