Organized by the Association for Computer Linguistics special interest group on linguistic data (SIGDAT), Empirical Methods in Natural Language Processing is a prominent conference in the area of Natural Language Processing. The conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019 was held in Hong Kong from November 3 to 7, 2019. NAVER Corporation attended the conference as a gold-level sponsor.
The following papers were accepted at the EMNLP-IJCNLP 2019.
| Subword Language Model for Query Auto-Completion | Gyuwan Kim | Subword language model for query auto-completion (QAC) to decode faster while maintaining close accuracy compared to the character language model baseline, and proposing a new evaluation metric for QAC. | arXiv Github |
| NL2pSQL: Generating Pseudo-SQL Queries from Under-specified Natural Language Questions | Fuxiang Chen, Seung-won Hwang, Jaegul Choo, Jung-Woo Ha, Sung Kim | A new dataset which has a better performance in managing and generating tables and is more applicable to the general situation than existing NL2SQL | Paper Github |
| Mixture Content Selection for Diverse Sequence Generation | Jaemin Cho*, Minjoon Seo, Hannaneh Hajishirzi | A new mixture-based model for the generation of diverse queries and summaries | arXiv Github |
Please see below for photos!
Minjoon Seo (Clova AI Research) participated in the Machine Reading for Question Answering (MRQA) workshop as a member of the organizing committee. To promote research on MRQA, the workshop sought submissions in two tracks: a research track and a new shared task track. The shared task of the workshop was specifically designed to test how well MRQA systems can generalize to new domains.
Media coverage on NAVER’s achievements at EMNLP-IJCNLP 2019:
- https://m.news.naver.com/read.nhn?mode=LSD&mid=sec&sid1=105&oid=018&aid=0004517503&fbclid=IwAR1TALjH314O4l8cjMUY-Pm1mKd_KlyvHrF8PDn81g7RXZM04Kve-lMzkDQ (in Korean)
네이버, 자연어처리 국제 학회 ‘EMNLP-IJCNLP 2019’ 에서 성과 공개 - https://papago.naver.net/website?locale=ko&source=ko&target=en&url=https%3A%2F%2Fm.news.naver.com%2Fread.nhn%3Fmode%3DLSD%26mid%3Dsec%26sid1%3D105%26oid%3D018%26aid%3D0004517503%26fbclid%3DIwAR1TALjH314O4l8cjMUY-Pm1mKd_KlyvHrF8PDn81g7RXZM04Kve-lMzkDQ
(in English – translated by Papago)