@samsja19: Very exciting work to bridge the gap between RL and mid/pretraining You can learn from your environment beyond the rewa…
Summary
A new method called ECHO bridges RL and pre-training by using next token prediction on tool call outputs to learn from the environment beyond reward signals, combining world modeling and agentic actions.
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Cached at: 06/12/26, 04:51 AM
Very exciting work to bridge the gap between RL and mid/pretraining
You can learn from your environment beyond the reward signal by doing next token prediction on some of your tool call output
Prime Intellect (@PrimeIntellect): True agents model the world.
Current training provides no separation between agent and environment: pre-training only trains world modeling, RL only agentic actions. We combine both using ECHO by @DimitrisPapail and @VaishShrivas.
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