WebTable 5: The experiments on single-text classification tasks with more than 5 labels. Different from previous experiments, we randomly select 8 samples for each label. PT … WebPPT: Pre-trained Prompt Tuning for Few-shot Learning Anonymous ACL submission Abstract Prompts for pre-trained language models 001 (PLMs) have shown remarkable …

[PDF] Learning a Better Initialization for Soft Prompts via Meta ...

WebSep 9, 2024 · Prompts for pre-trained language models (PLMs) have shown remarkable performance by bridging the gap between pre-training tasks and various downstream … WebTherefore, in this work, we propose to pre-train prompts by adding soft prompts into the pre-training stage to obtain a better initialization. We name this Pre-trained Prompt Tuning framework "PPT". To ensure the generalization of PPT, we formulate similar classification tasks into a unified task form and pre-train soft prompts for this unified ... jonarve warehouse operative

PPT: Pre-trained Prompt Tuning for Few-shot Learning - YouTube

Web1. Downstream Task Group으로 Soft Prompt를 Pre-train해서 Prompt Initialization으로 사용하는 방법론을 제안. 2. PPT는 Few-shot Setting에서 Vanilla Prompt Tuning 보다 높은 … http://nlp.csai.tsinghua.edu.cn/documents/230/PPT_Pre-trained_Prompt_Tuning_for_Few-shot_Learning.pdf WebPPT: Pre-trained Prompt Tuning for Few-shot Learning. Yuxian Gu*, Xu Han*, Zhiyuan Liu, Minlie Huang. , 2024.9. Differentiable Prompt Makes Pre-trained Language Models Better … jonas activity