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The Devil is in the Details: Evaluating Limitations of Transformer-based
  Methods for Granular Tasks

The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks

2 November 2020
Brihi Joshi
Neil Shah
Francesco Barbieri
Leonardo Neves
ArXivPDFHTML

Papers citing "The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks"

2 / 2 papers shown
Title
Guiding Generative Language Models for Data Augmentation in Few-Shot
  Text Classification
Guiding Generative Language Models for Data Augmentation in Few-Shot Text Classification
A. Edwards
Asahi Ushio
Jose Camacho-Collados
Hélène de Ribaupierre
Alun D. Preece
VLM
13
23
0
17 Nov 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
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
6,959
0
20 Apr 2018
1