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1 claim from 1 paper

1. Computer Science › Topic Modeling

   UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training

   Bao, Dong, Wei et al. · arXiv (Cornell University) · 2020

   The paper proposes pseudo-masked language models (PMLM), a training method that pre-trains one model for both autoencoding and partially autoregressive tasks, and reports strong benchmark results.

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   1. UncheckedLanguage models pre-trained with PMLM reached new state-of-the-art results on many language understanding and generation benchmarks, per the authors.“Our experiments show that the unified language models pre-trained using PMLM achieve new state-of-the-art results on a wide range of natural language understanding and generation tasks across several widely used benchmarks.”