Exploiting the Potential of Seq2Seq Models as Robust Few-Shot Learners

27 July 2023

Papers citing "Exploiting the Potential of Seq2Seq Models as Robust Few-Shot Learners"

7 / 7 papers shown

Title
GLM-130B: An Open Bilingual Pre-trained Model Aohan Zeng Xiao Liu Zhengxiao Du Zihan Wang Hanyu Lai ... Jidong Zhai Wenguang Chen Peng-Zhen Zhang Yuxiao Dong Jie Tang BDL LRM 245 1,071 0 05 Oct 2022
Bidirectional Language Models Are Also Few-shot Learners Ajay Patel Bryan Li Mohammad Sadegh Rasooli Noah Constant Colin Raffel Chris Callison-Burch LRM 62 45 0 29 Sep 2022
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts Stephen H. Bach Victor Sanh Zheng-Xin Yong Albert Webson Colin Raffel ... Khalid Almubarak Xiangru Tang Dragomir R. Radev Mike Tian-Jian Jiang Alexander M. Rush VLM 225 338 0 02 Feb 2022
Multitask Prompted Training Enables Zero-Shot Task Generalization Victor Sanh Albert Webson Colin Raffel Stephen H. Bach Lintang Sutawika ... T. Bers Stella Biderman Leo Gao Thomas Wolf Alexander M. Rush LRM 211 1,656 0 15 Oct 2021
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation Ofir Press Noah A. Smith M. Lewis 245 695 0 27 Aug 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,843 0 18 Apr 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 248 1,986 0 31 Dec 2020