Our two papers (a long paper and a system demonstration paper) were accepted at the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), a top-tier academic conference on natural language processing.

LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention.
Ikuya Yamada, Akari Asai (University of Washington), Hiroyuki Shindo (NAIST), Hideaki Takeda (NII) and Yuji Matsumoto (RIKEN AIP)
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020

Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia.
Ikuya Yamada, Akari Asai (University of Washington), Jin Sakuma (The University of Tokyo), Hiroyuki Shindo (NAIST), Hideaki Takeda (NII), Yoshiyasu Takefuji (Keio University), Yuji Matsumoto (RIKEN AIP)
Conference on Empirical Methods in Natural Language Processing (EMNLP), system demonstrations, 2020