Quantifying Adaptability in Pre-trained Language Models with 500 Tasks

Quantifying Adaptability in Pre-trained Language Models with 500 Tasks

6 December 2021

Madian Khabsa

Luke Zettlemoyer

Papers citing "Quantifying Adaptability in Pre-trained Language Models with 500 Tasks"

7 / 7 papers shown

Title
Generative Models as a Complex Systems Science: How can we make sense of large language model behavior? Ari Holtzman Peter West Luke Zettlemoyer AI4CE 30 13 0 31 Jul 2023
COLLIE: Systematic Construction of Constrained Text Generation Tasks Shunyu Yao Howard Chen Austin W. Hanjie Runzhe Yang Karthik Narasimhan 42 32 0 17 Jul 2023
State-of-the-art generalisation research in NLP: A taxonomy and review Dieuwke Hupkes Mario Giulianelli Verna Dankers Mikel Artetxe Yanai Elazar ... Leila Khalatbari Maria Ryskina Rita Frieske Ryan Cotterell Zhijing Jin 114 93 0 06 Oct 2022
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 238 805 0 14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,844 0 18 Apr 2021
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 415 2,584 0 03 Sep 2019
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 297 6,956 0 20 Apr 2018