PRO-Step: Step-level Process Reward Optimization for Retrieval-Augmented Generation
cs.CL, cs.AI
Submitted: 2026-08-31
Updated: 2026-08-31
Code: https://github.com/keemminnke/PRO-Step
Terminology
Sources
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- GPT-4o System Card
- Improve Mathematical Reasoning in Language Models by Automated Process Supervision
- Qwen2.5 Technical Report
- Qwen3 Technical Report
- OpenAI GPT-5 System Card
- Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG
- R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
- GenPRM: Scaling Test-Time Compute of Process Reward Models via Generative Reasoning
- ProRAG: Process-Supervised Reinforcement Learning for Retrieval-Augmented Generation
- Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models
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