P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

14 October 2021

Xiao Liu

Papers citing "P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks"

20 / 70 papers shown

Title
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models Robert L Logan IV Ivana Balavzević Eric Wallace Fabio Petroni Sameer Singh Sebastian Riedel VPVLM 68 209 0 24 Jun 2021
PTR: Prompt Tuning with Rules for Text Classification Xu Han Weilin Zhao Ning Ding Zhiyuan Liu Maosong Sun VLM 79 519 0 24 May 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 448 3,952 0 18 Apr 2021
Learning How to Ask: Querying LMs with Mixtures of Soft Prompts Guanghui Qin J. Eisner 32 538 0 14 Apr 2021
Better Feature Integration for Named Entity Recognition Lu Xu Zhanming Jie Wei Lu Lidong Bing 39 38 0 12 Apr 2021
Factual Probing Is [MASK]: Learning vs. Learning to Recall Zexuan Zhong Dan Friedman Danqi Chen 34 407 0 12 Apr 2021
Prefix-Tuning: Optimizing Continuous Prompts for Generation Xiang Lisa Li Percy Liang 164 4,167 0 01 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 340 1,950 0 31 Dec 2020
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters Mengjie Zhao Yi Zhu Ehsan Shareghi Ivan Vulić Roi Reichart Anna Korhonen Hinrich Schütze 66 64 0 31 Dec 2020
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners Timo Schick Hinrich Schütze 86 966 0 15 Sep 2020
Self-supervised Learning: Generative or Contrastive Xiao Liu Fanjin Zhang Zhenyu Hou Zhaoyu Wang Li Mian Jing Zhang Jie Tang SSL 96 1,604 0 15 Jun 2020
DeBERTa: Decoding-enhanced BERT with Disentangled Attention Pengcheng He Xiaodong Liu Jianfeng Gao Weizhu Chen AAML 98 2,682 0 05 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 467 41,106 0 28 May 2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 258 19,824 0 23 Oct 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 394 24,160 0 26 Jul 2019
XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang Zihang Dai Yiming Yang J. Carbonell Ruslan Salakhutdinov Quoc V. Le AI4CE 178 8,386 0 19 Jun 2019
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Alex Jinpeng Wang Yada Pruksachatkun Nikita Nangia Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 174 2,287 0 02 May 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 919 93,936 0 11 Oct 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 629 7,080 0 20 Apr 2018
SQuAD: 100,000+ Questions for Machine Comprehension of Text Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang RALM 144 8,067 0 16 Jun 2016