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The Right Model for the Job: An Evaluation of Legal Multi-Label
  Classification Baselines

The Right Model for the Job: An Evaluation of Legal Multi-Label Classification Baselines

22 January 2024
Martina Forster
Claudia Schulz
Prudhvi Nokku
Melicaalsadat Mirsafian
Jaykumar Kasundra
Stavroula Skylaki
    AILaw
    ELM
ArXivPDFHTML

Papers citing "The Right Model for the Job: An Evaluation of Legal Multi-Label Classification Baselines"

4 / 4 papers shown
Title
Pile of Law: Learning Responsible Data Filtering from the Law and a
  256GB Open-Source Legal Dataset
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Peter Henderson
M. Krass
Lucia Zheng
Neel Guha
Christopher D. Manning
Dan Jurafsky
Daniel E. Ho
AILaw
ELM
127
94
0
01 Jul 2022
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
Ilias Chalkidis
Abhik Jana
D. Hartung
M. Bommarito
Ion Androutsopoulos
Daniel Martin Katz
Nikolaos Aletras
AILaw
ELM
123
244
0
03 Oct 2021
Mixout: Effective Regularization to Finetune Large-scale Pretrained
  Language Models
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models
Cheolhyoung Lee
Kyunghyun Cho
Wanmo Kang
MoE
222
204
0
25 Sep 2019
Neural Legal Judgment Prediction in English
Neural Legal Judgment Prediction in English
Ilias Chalkidis
Ion Androutsopoulos
Nikolaos Aletras
AILaw
ELM
98
279
0
05 Jun 2019
1