Verified75% confidenceFactTime unknown
The GPT series adopts the autoregressive training objective of "predicting the next word".
5
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75%
Confidence
Long-term
Relevance
6/1/2026
First Seen
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Related Claims
UnverifiedSelf-supervised learning is the training foundation of the GPT series of models, which learn by predicting the next masked word in text.82% similarVerifiedThe GPT series of models are trained on trillion-scale text data through a self-supervised task of predicting the next token.81% similarVerifiedThe GPT series of models uses an autoregressive generation approach, predicting the next most likely output token by token.80% similarUnverifiedGPT-series models are optimized during training to maximize prediction accuracy (i.e., minimize perplexity), so their outputs tend toward high-probability word combinations.80% similarVerifiedGPT-5.6 is the result of the continued expansion of the reasoning paradigm, achieving a capability leap by simultaneously scaling reinforcement learning and pre-training.79% similar
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