Aligning Word Embeddings from BERT to Vocabulary-Free Representations-Reference-Cited by-同舟云学术

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Aligning Word Embeddings from BERT to Vocabulary-Free Representations

Published:2023-07-24 Issue: Volume:1 Page:108-115
ISSN:
Container-title:2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)
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Author:

Perez Alejandro Rodriguez¹,Sooksatra Korn¹,Rivas Pablo¹,Quevedo Ernesto¹,Turek Javier²,Bichler Gisela³,Cerny Tomas¹,Giddens Laurie⁴,Petter Stacie⁵

Affiliation:

1. School of Eng. & Computer Science Baylor University,Dept. of Computer Science

2. Intel Corporation,Intel Labs,Portland,Oregon

3. School of Criminology & Criminal Justice California State University,San Bernardino

4. College of Business, Information Tech. & Decisions Sci. University of North Texas,Dept. G. Brint Ryan

5. School of Business Management of Information Systems Wake Forest University

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10487132/10487174/10487519.pdf?arnumber=10487519

Reference46 articles.

1. Neural Architecture Search for Transformers: A Survey

2. Understanding and overcoming the challenges of efficient transformer quantization;Bondarenko

3. BERT: Pre-training of deep bidirectional transformers for language understanding;Devlin,2019

4. Language models are unsupervised multitask learners;Radford;OpenAI blog,2019

5. Byte pair encoding is suboptimal for language model pretraining;Bostrom,2020

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