浅井明里 / Akari Asai (University of Washington)
[Webサイト]ワシントン大学コンピューターサイエンス博士課程に在籍．2019年東京大学工学部電子情報工学科卒業．自然言語処理，主に質問応答や多言語自然言語処理等の研究に従事．
概要
Multilingual question answering tasks typically assume answers exist in the same language as the question. Yet in practice, many languages face both information scarcity---where languages have few reference articles---and information asymmetry---where questions reference concepts from other cultures. This work extends open-retrieval question answering to a cross-lingual setting enabling questions from one language to be answered via answer content from another language. We construct a large-scale dataset built on questions from TyDi QA lacking same-language answers. Our task formulation, called Cross-lingual Open Retrieval Question Answering (XOR QA), includes 40k information-seeking questions from across 7 diverse non-English languages. Based on this dataset, we introduce three new tasks that involve cross-lingual document retrieval using multi-lingual and English resources. We establish baselines with state-of-the-art machine translation systems and cross-lingual pretrained models. Experimental results suggest that XOR QA is a challenging task that will facilitate the development of novel techniques for multilingual question answering.
※トークは日本語です。