specific method · filed under post-training
Sample Mixer
Mixes samples with dynamic sampling and partial rollout to stabilize per-task composition in training batches.
Also called A sample mixing mechanism.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
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A sample mixing mechanism, working together with dynamic sampling and partial rollout, stabilizes per-task sample composition in train batches.
usedsoftware implementationin MiMo-V2.6 RL infrastructureXiaomi
Filed alongside
Other methods under post-training :: rollout & RL infrastructure.
Asynchronous reinforcement learningPartial rolloutAsynchronous RL frameworks for large-scale agent scaffolds and environment orchestrationToken-in-token-out (TITO)Asynchronous reinforcement learning infrastructureCo-located RL trainingData SchedulerDecoupled control plane and data planeDecoupling agent rollout into sandbox and worker containerDeficit-corrected schedulingLarge-scale asynchronous RL in synthesized tasksOne-step off-policy asynchronous reinforcement learningPredictive Rollout DispatchSample-grained garbage collectionSeamless Rollout EngineSLIMEToken-granularity persistence of rollout statesToken-level interruptionTool ManagerToolboxAdaptive Rollout ConcurrencyAdaptive Rollout SchedulingAgent LoopAgent-centric rollout execution