Should We Be Pre-training? An Argument for End-task Aware Training as an
Alternative

Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative

15 September 2021

Ameet Talwalkar

Graham Neubig

Papers citing "Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative"

10 / 10 papers shown

Title
Avoid Overthinking in Self-Supervised Models for Speech Recognition Dan Berrebbi Brian Yan Shinji Watanabe LRM 13 4 0 01 Nov 2022
AANG: Automating Auxiliary Learning Lucio Dery Paul Michel M. Khodak Graham Neubig Ameet Talwalkar 36 9 0 27 May 2022
Learning to Scaffold: Optimizing Model Explanations for Teaching Patrick Fernandes Marcos Vinícius Treviso Danish Pruthi André F. T. Martins Graham Neubig FAtt 17 22 0 22 Apr 2022
Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment Mu Yang K. Hirschi S. Looney Okim Kang John H. L. Hansen 32 15 0 29 Mar 2022
NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework Xingcheng Yao Yanan Zheng Xiaocong Yang Zhilin Yang 30 44 0 07 Nov 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science Charlotte Loh T. Christensen Rumen Dangovski Samuel Kim Marin Soljacic 24 16 0 15 Oct 2021
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP Timo Schick Sahana Udupa Hinrich Schütze 259 374 0 28 Feb 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 290 1,814 0 14 Dec 2020
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
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,681 0 09 Mar 2017