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  "text": "Introducing Reinforcement Learning from Collective Rewards (RLCR).\n\nRLCR is a recipe that trains language models as agent organisations, which share a message board and workspace. We use it to train Avalon-M1-Mini (120B) and study its behaviour.\n\nWe find a number of interesting results, including:\n\n🛠️ Learnt organisational hierarchies and divisions of labour\n🕵️ Increased collective verification, through hires of verifiers and testers\n👥 The rise of collective thinking, where agents think more about other agents and how to help them\n\nWe believe RLCR can provide a laboratory for studying collective intelligence and multi-agent safety.\n\nBlog post and technical report 👇",
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