Details

Autor(en) / Beteiligte

• Treviso, Marcos
• Lee, Ji-Ung
• Ji, Tianchu
• Aken, Betty van
• Cao, Qingqing
• Ciosici, Manuel R.
• Hassid, Michael
• Heafield, Kenneth
• Hooker, Sara
• Raffel, Colin
• Martins, Pedro H.
• Martins, André F. T.
• Forde, Jessica Zosa
• Milder, Peter
• Simpson, Edwin
• Slonim, Noam
• Dodge, Jesse
• Strubell, Emma
• Balasubramanian, Niranjan
• Derczynski, Leon
• Gurevych, Iryna
• Schwartz, Roy

Titel

Efficient Methods for Natural Language Processing: A Survey

Ist Teil von

• Transactions of the Association for Computational Linguistics, 2023-07, Vol.11, p.826-860

Ort / Verlag

One Broadway, 12th Floor, Cambridge, Massachusetts 02142, USA: MIT Press

Erscheinungsjahr

2023

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources include data, time, storage, or energy, all of which are naturally limited and unevenly distributed. This motivates research into methods that require fewer resources to achieve similar results. This survey synthesizes and relates current methods and findings in efficient NLP. We aim to provide both guidance for conducting NLP under limited resources, and point towards promising research directions for developing more efficient methods.