Agentic RL for LLMs: Best Practices & Datasets скачать в хорошем качестве

Agentic RL for LLMs: Best Practices & Datasets

In this AI Research Roundup episode, Alex discusses the paper: 'Demystifying Reinforcement Learning in Agentic Reasoning(2510.11701v1)' This study systematically examines how reinforcement learning enhances agentic reasoning in LLMs across data, algorithms, and reasoning modes. It finds that real end-to-end tool-use trajectories and high-diversity, model-aware datasets provide stronger SFT starts and better RL performance. Exploration-friendly techniques—like higher clipping, extended reward shaping, and sufficient policy entropy—boost training efficiency. It also shows a deliberative strategy with fewer tool calls improves tool efficiency and final accuracy, and releases new SFT and RL datasets that enable strong results with smaller models. Paper URL: https://arxiv.org/pdf/2510.11701 #AI #MachineLearning #DeepLearning #ReinforcementLearning #LLM #AgenticReasoning #ToolUse #SFT Resources: GitHub: https://github.com/Gen-Verse/Open-Age...