BBTv2: Towards a Gradient-Free Future with Large Language Models

BBTv2: Towards a Gradient-Free Future with Large Language Models

23 May 2022

Tianxiang Sun

Xuanjing Huang

Xipeng Qiu

Papers citing "BBTv2: Towards a Gradient-Free Future with Large Language Models"

7 / 7 papers shown

Title
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 206 604 0 14 Oct 2021
Paradigm Shift in Natural Language Processing Tianxiang Sun Xiangyang Liu Xipeng Qiu Xuanjing Huang 100 71 0 26 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 254 2,999 0 18 Apr 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 256 991 0 17 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 223 1,649 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 228 1,382 0 21 Jan 2020
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 267 6,003 0 20 Apr 2018