AdapterEM: Pre-trained Language Model Adaptation for Generalized Entity Matching using Adapter-tuning-Reference-Cited by-同舟云学术

AdapterEM: Pre-trained Language Model Adaptation for Generalized Entity Matching using Adapter-tuning

Published:2023-05-05 Issue: Volume: Page:
ISSN:
Container-title:International Database Engineered Applications Symposium Conference
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Author:

Mugeni John Bosco¹^ORCID,Lynden Steven²^ORCID,Amagasa Toshiyuki³^ORCID,Matono Akiyoshi²^ORCID

Affiliation:

1. Computer Science Department, Systems and Information Engineering, University of Tsukuba, Japan and Data platform research team, National Institute of Advanced Industrial Science and Technology (AIST), Japan

2. Data platform research team, National Institute of Advanced Industrial Science and Technology (AIST), Japan

3. Computer Science department, Systems and Information Engineering, University Of Tsukuba, Japan

Funder

NEDO

JST CREST

JSPS KAKENHI

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589462.3589498

Reference33 articles.

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2. Geospatial Entity Resolution

3. Samuel R Bowman Gabor Angeli Christopher Potts and Christopher D Manning. 2015. A large annotated corpus for learning natural language inference. arXiv preprint arXiv:1508.05326. Samuel R Bowman Gabor Angeli Christopher Potts and Christopher D Manning. 2015. A large annotated corpus for learning natural language inference. arXiv preprint arXiv:1508.05326.

4. Ursin Brunner and Kurt Stockinger . 2020 . Entity Matching with Transformer Architectures - A Step Forward in Data Integration. In International Conference on Extending Database Technology. Ursin Brunner and Kurt Stockinger. 2020. Entity Matching with Transformer Architectures - A Step Forward in Data Integration. In International Conference on Extending Database Technology.

5. Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. https://doi.org/10.48550/ARXIV.1810.04805 10.48550/ARXIV.1810.04805 Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. https://doi.org/10.48550/ARXIV.1810.04805

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