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 […]
Tag: EMNLP2019
Subword Language Model for Query Auto-Completion (EMNLP-IJCNLP 2019)
Gyuwan Kim arXiv Github Motivations to Faster Neural Query Auto-Completion When browsing on search engines, such as NAVER, users type in the information which they want to look for. Query auto-completion (QAC) suggests most likely completion candidates when a user enters the input. It is one of the essential features of search engines. In this […]
Mixture Content Selection for Diverse Sequence Generation (EMNLP-IJCNLP 2019)
Mixture Content Selection for Diverse Sequence Generation (EMNLP 2019) Jaemin Cho, Minjoon Seo, Hannaneh Hajishirzi arXiv Github Seq2Seq is not for One-to-Many Mapping Comparison between the standard encoder-decoder model and ours An RNN Encoder-Decoder (Seq2Seq) model is widely used for sequence generation, in particular, machine translation in which neural models are as competent as human […]
EMNLP-IJCNLP 2019
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 will be held in […]