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Stanford U’s Language Model Leverages Stochastic Processes to Improve Efficiency and Coherence in Long Text Generation
March 31, 2022, 4:46 p.m. | Synced
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A Stanford research team proposes Time Control (TC), a language model that implicitly plans via a latent stochastic process and generates texts consistent with this latent plan to improve performance on long text generation.
The post Stanford U’s Language Model Leverages Stochastic Processes to Improve Efficiency and Coherence in Long Text Generation first appeared on Synced.
ai artificial intelligence language language model machine learning machine learning & data science ml processes research stanford stochastic stochastic process technology text text generation
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