An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language Processing

Abdul Moeed, Gerhard Hagerer, Sumit Dugar, Sarthak Gupta, Mainak Ghosh, Hannah Danner, Oliver Mitevski, Andreas Nawroth, Georg Groh

Abstract
A major challenge in modern neural networks is the utilization of previous knowledge for new tasks in an effective manner, otherwise known as transfer learning. Fine-tuning, the most widely used method for achieving this, suffers from catastrophic forgetting. The problem is often exacerbated in natural language processing (NLP). In this work, we assess progressive neural networks (PNNs) as an alternative to fine-tuning. The evaluation is based on common NLP tasks such as sequence labeling and text classification. By gauging PNNs across a range of architectures, datasets, and tasks, we observe improvements over the baselines throughout all experiments.
Anthology ID:
2020.lrec-1.172
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1376–1381
Language:
English
URL:
https://preview.aclanthology.org/icon-24-ingestion/2020.lrec-1.172/
DOI:
Bibkey:
Cite (ACL):
Abdul Moeed, Gerhard Hagerer, Sumit Dugar, Sarthak Gupta, Mainak Ghosh, Hannah Danner, Oliver Mitevski, Andreas Nawroth, and Georg Groh. 2020. An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language Processing. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1376–1381, Marseille, France. European Language Resources Association.
Cite (Informal):
An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language Processing (Moeed et al., LREC 2020)
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PDF:
https://preview.aclanthology.org/icon-24-ingestion/2020.lrec-1.172.pdf
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