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GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Wang et al., 2019, GLUE (7th International Conference on Learning Representations (ICLR 2019))

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5 Baselines

  1. What baseline models did GLUE evaluate?
    A two-layer BiLSTM encoder with max pooling over GloVe embeddings, with sentence pairs as \([u; v; |u - v|; u * v]\); variants with cross-sentence attention, ELMo and CoVe; trained per task or multi-task (tasks sampled in proportion to data size). Also pretrained sentence encoders: CBoW, Skip-Thought, InferSent, DisSent, GenSen.
    • Wang et al., 2019, GLUE (7th International Conference on Learning Representations (ICLR 2019)), §5

Source

  • Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy and Samuel R. Bowman. 2019. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. In 7th International Conference on Learning Representations (ICLR 2019). https://openreview.net/forum?id=rJ4km2R5t7