Large Language Models are Zero-Shot Reasoners

24 May 2022

Papers citing "Large Language Models are Zero-Shot Reasoners"

8 / 308 papers shown

Title
Show Your Work: Scratchpads for Intermediate Computation with Language Models Maxwell Nye Anders Andreassen Guy Gur-Ari Henryk Michalewski Jacob Austin ... Aitor Lewkowycz Maarten Bosma D. Luan Charles Sutton Augustus Odena ReLM LRM 135 728 0 30 Nov 2021
Do Prompt-Based Models Really Understand the Meaning of their Prompts? Albert Webson Ellie Pavlick LRM 84 361 0 02 Sep 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 326 1,343 0 17 Jan 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 388 2,051 0 31 Dec 2020
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners Timo Schick Hinrich Schütze 90 970 0 15 Sep 2020
Unsupervised Commonsense Question Answering with Self-Talk Vered Shwartz Peter West Ronan Le Bras Chandra Bhagavatula Yejin Choi ReLM SSL AI4MH LRM 43 261 0 11 Apr 2020
Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems Wang Ling Dani Yogatama Chris Dyer Phil Blunsom AIMat 54 701 0 11 May 2017
Pointer Sentinel Mixture Models Stephen Merity Caiming Xiong James Bradbury R. Socher RALM 180 2,814 0 26 Sep 2016