Web: http://arxiv.org/abs/2209.09401

Sept. 21, 2022, 1:14 a.m. | Zichun Yu, Tianyu Gao, Zhengyan Zhang, Yankai Lin, Zhiyuan Liu, Maosong Sun, Jie Zhou

cs.CL updates on arXiv.org arxiv.org

Prompting, which casts downstream applications as language modeling tasks,
has shown to be sample efficient compared to standard fine-tuning with
pre-trained models. However, one pitfall of prompting is the need of
manually-designed patterns, whose outcome can be unintuitive and requires large
validation sets to tune. To tackle the challenge, we propose AutoSeq, a fully
automatic prompting method: (1) We adopt natural language prompts on
sequence-to-sequence models, enabling free-form generation and larger label
search space; (2) We propose label sequences -- …

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