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Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward

cs.AI updates on arXiv.org·
AI Analysis

A new framework called DecomposeR enhances long-form research tasks for large language models by structuring research plans as directed acyclic graphs, improving planning and execution. This approach has shown to outperform existing models by 5.1-8.0 points on key benchmarks, indicating a significant advancement in AI research capabilities.

Key Topics

DecomposeRQwen3-8Blarge language modelsreinforcement learning

Originally reported by cs.AI updates on arXiv.org. Read the full article ↗

Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward | AI Crypto Daily Wire