Showing cs.AIShow all
2 papers · 1 filter
cs.AI2026
PlanningBench: Generating Scalable and Verifiable Planning Data for Evaluating and Training Large Language Models
Ziliang Zhao, Zenan Xu, Shuting Wang +7
Planning is a fundamental capability for large language models (LLMs) because such complex tasks require models to coordinate goals, constraints, resources, and long-term consequen…
cs.AI2026
ProRAG: Process-Supervised Reinforcement Learning for Retrieval-Augmented Generation
Zhao Wang, Ziliang Zhao, Zhicheng Dou
Reinforcement learning (RL) has become a promising paradigm for optimizing Retrieval-Augmented Generation (RAG) in complex reasoning tasks. However, traditional outcome-based RL ap…