Beyond Prompting: Making Pre-trained Language Models Better Zero-shot
Learners by Clustering Representations

Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations

29 October 2022

Roger Wattenhofer

Mrinmaya Sachan

Papers citing "Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations"

6 / 6 papers shown

Title
Weakly-supervised Text Classification Based on Keyword Graph Lu Zhang Jiandong Ding Yi Xu Yingyao Liu Shuigeng Zhou OffRL OOD 36 57 0 06 Oct 2021
RAFT: A Real-World Few-Shot Text Classification Benchmark Neel Alex Eli Lifland Lewis Tunstall A. Thakur Pegah Maham ... Carolyn Ashurst Paul Sedille A. Carlier M. Noetel Andreas Stuhlmuller RALM 166 56 0 28 Sep 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 238 1,898 0 31 Dec 2020
Efficient Intent Detection with Dual Sentence Encoders I. Casanueva Tadas Temvcinas D. Gerz Matthew Henderson Ivan Vulić VLM 164 444 0 10 Mar 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 248 1,382 0 21 Jan 2020
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 29,632 0 16 Jan 2013