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Forget data labeling: Tencent’s R-Zero shows how LLMs can train themselves
By using two co-evolving AI models, the R-Zero framework generates its own learning curriculum, moving beyond the need for labeled datasets.
A new training framework developed by researchers at Tencent AI Lab and Washington University in St. Louis enables large language models (LLMs) to improve themselves without requiring any human-labeled data. Turning energy into a strategic advantage Architecting efficient inference for real throughput gains Unlocking competitive ROI with sustainable AI systems In written comments to VentureBeat, Chengsong Huang, co-author of the paper and a doctoral student at Washington University in St. Louis, explained that this dynamic is crucial because generating high-quality questions is often more complicated than finding the answers.
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