Dual Encoder Training Method for Product Matching Accepted at EMNLP 2023 in the Industry Track
We are thrilled to announce that a research paper authored by Justin Chiu at Rakuten Institute of Technology in Boston has been accepted for presentation at the EMNLP 2023 conference in the industry track. EMNLP 2023 stands as the premier conference in the field of Computational Linguistics and Natural Language Processing.
Justin’s paper, titled “Retrieval-Enhanced Dual Encoder Training for Product Matching”, introduces a two-stage training for the dual encoder model which promises to enhance the accuracy and efficiency of product matching in various applications, including e-commerce and recommendation systems. This is a significant step forward in delivering better user experiences and more personalized recommendations.
The conference will be held from 06-10 December in Singapore.