implementation detail · filed under data curation
Smooth weighted round-robin source scheduling
Uses smooth weighted round-robin to schedule sources according to their weights.
Also called smooth weighted round-robin.
- source
- 1
- models
- 2
- lab adopt it
- 1
- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
These weights drive smooth weighted round-robin
usedunclearin MiMo-V2.6 RL and OPD infrastructure
Filed alongside
Other methods under data curation :: data mixture & curriculum.
AutoMixerDeterministic pre-splitting of ultra-long documentsVulnerability-discovery data inclusionAgent-centric multimodal data mixtureAttribution, hedging, and refusal data subsetsBlind pairwise bucket-boundary calibrationData SchedulerDomain-specific multimodal datasetsDynamic sampling for mixed-task reinforcement learningFiltering, deduplication, and difficulty calibrationGaussian-based data mixture and curriculum constructionInterleaved dataInterleaved multimodal trainingKL-regularized data-mixture optimizationLong-context data upsamplingPass-rate-based RL task samplingPrior-constrained Dirichlet mixture explorationProtocolQA-aligned RL training datasetsSample MixerScaling-ladder-guided data and model planningText-only pre-training corpusThree-stage data mixture strategyThree-stage pre-training curriculumTwo-phase curriculum