MetaICL: Learning to Learn In Context

MetaICL: Learning to Learn In Context

29 October 2021

Luke Zettlemoyer

Hannaneh Hajishirzi

Papers citing "MetaICL: Learning to Learn In Context"

9 / 359 papers shown

Title
Finetuned Language Models Are Zero-Shot Learners Jason W. Wei Maarten Bosma Vincent Zhao Kelvin Guu Adams Wei Yu Brian Lester Nan Du Andrew M. Dai Quoc V. Le ALM UQCV 31 3,561 0 03 Sep 2021
Do Prompt-Based Models Really Understand the Meaning of their Prompts? Albert Webson Ellie Pavlick LRM 30 352 0 02 Sep 2021
CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP Qinyuan Ye Bill Yuchen Lin Xiang Ren 209 179 0 18 Apr 2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 277 1,120 0 18 Apr 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 269 1,812 0 14 Dec 2020
Explainable Automated Fact-Checking for Public Health Claims Neema Kotonya Francesca Toni 216 249 0 19 Oct 2020
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 408 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 6,950 0 20 Apr 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 281 11,681 0 09 Mar 2017