specific method · filed under post-training
Multi-environment reinforcement learning from verifiable rewards
Reinforcement learning from verifiable rewards applied across a mix of environments.
Also called multi-environment RLVR.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
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Evidence
1 span quoted from the sources, strongest treatment first.
unified RLVR over a wide mix of reasoning, agentic, code, safety, usability, and chat environments
usedpost trainingin Nemotron 3 UltraNVIDIA
Filed alongside
Other methods under post-training :: agentic post-training.
Agentic reinforcement learningMulti-harness trainingAgentic tool-use trainingEnvironment hardeningReinforcement learning on synthetic agentic dataRepair-agent environment correction loopAgentic post-trainingAutonomous Execution Tasks (AET)Concurrent multi-environment post-trainingContainer-level network isolationEnvironment preparation to prevent solution leakageEnvironment scaling for realistic training tasksGenerate-verify-refine loopHarness-optimized trainingMock applications for personal-assistant reinforcement learningMulti-agent task decomposition and coordinationMulti-environment reinforcement learningMulti-harness trajectory training with native behavior preservationMulti-turn collaboration simulatorProduction-harness-matched reinforcement learningPython tool use in chain-of-thoughtRe-post-training for agentic capabilitiesReinforcement learning in an agent harnessReinforcement learning restricted to search and code environments