AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction

By Xiang Chen, Ningyu Zhang, Jiahuan Yan, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen. 2021

Subfields: Prompting & Reasoning, Information Extraction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Prompting & Reasoning

1. Swaroop Mishra
2. Mihir Parmar
3. Chitta Baral
4. Ravsehaj Singh Puri
5. Zhiyuan Liu
6. Maosong Sun
7. Ning Ding
8. Shengding Hu

In Information Extraction

1. Maosong Sun
2. Zhilin Yang
3. Jie Tang
4. Xiao Liu
5. Zhiyuan Liu
6. Zhengxiao Du

Citations in the corpus

• P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks (2021, background): “, 2021a), relation extraction (Chen et al., 2021a; Han et al., 2021b; Sainz et al., 2021), knowledge probing (Zhong et al.”
• P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks (2022, background): “Lester et al. (2021); Liu et al. (2021) have been proved quite effective in many NLP applications (Wang et al., 2021a,b; Chen et al., 2021; Zheng et al., 2021; Min et al., 2021), but still fall short at replacing fine-tuning due to lack of universality, as discussed below.”
• How Many Data Samples is an Additional Instruction Worth? (2022, background): “…learning to solve various tasks including text classification (Yin et al., 2019), Natural Language Inference (NLI) (Schick and Schütze, 2020), Question Answering (QA) (Jiang et al., 2020), Information Extraction (IE) (Chen et al., 2021; Cui et al., 2021) and many more (Liu et al., 2021).”
• Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification (2021, background): “, 2021) , Relation Extraction (Han et al., 2021; Chen et al., 2021), and Knowledge Probing (Petroni et al.”
• Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning (2021, unknown): “Prompt-based tuning [31, 19, 9, 21, 13, 6, 41, 2, 23], which has improved empirical downstream performance for lightweight adaptation methods beyond head tuning to approach full finetuning, is an important focus of our theoretical analysis.”
• HELP ME THINK: A Simple Prompting Strategy for Non-experts to Create Customized Content with Models (2022, background): “, 2022), relation extraction (Chen et al., 2021), biomedical applications (Parmar et al.”