PTR: Prompt Tuning with Rules for Text Classification-Reference-Cited by-同舟云学术

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PTR: Prompt Tuning with Rules for Text Classification

Published:2022 Issue: Volume:3 Page:182-192
ISSN:2666-6510
Container-title:AI Open
language:en
Short-container-title:AI Open

Author:

Han Xu^ORCID,Zhao Weilin^ORCID,Ding Ning,Liu Zhiyuan^ORCID,Sun Maosong

Funder

National Natural Science Foundation of China

Tsinghua University

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Software,Information Systems,Human-Computer Interaction,Computer Vision and Pattern Recognition,Computer Science Applications,Artificial Intelligence

Reference66 articles.

1. Towards a human-like open-domain chatbot;Adiwardana,2020

2. TACRED revisited: A thorough evaluation of the TACRED relation extraction task;Alt,2020

3. Matching the blanks: Distributional similarity for relation learning;Baldini Soares,2019

4. Curriculum learning;Bengio,2009

5. Language models are few-shot learners;Brown,2020

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