报告题目：Towards Unsupervised Machine Translation
报告时间：2021年12月31日（星期五）下午16：00
报告地点：校本部升华南楼102
报告人：上海交通大学 王瑞博士
报告摘要：Machine translation (MT) is a classic topic in NLP and AI. From 2010s when abundant computational resources became available, neural machine translation (NMT) reached state-of-the-art performance. Recently, unsupervised NMT (UNMT), which only relies on mono-lingual corpora, has achieved impressive results. Meanwhile, there are still several challenges for UNMT. This talk first introduces the background and the latest progress of UNMT. We then examine a number of challenges to UNMT and give empirical results on how well the technology currently holds up.
报告人简介: 王瑞，上海交通大学长聘教轨副教授、博士生导师，此前在日本情报通信研究机构（NICT）担任长聘研究员，研究方向是机器翻译和自然语言处理。他在ACL, EMNLP, ICLR, AAAI, IJCAI, TPAMI, TASLP等国际权威会议和期刊发表论文40余篇，在EACL和 EMNLP上开设了机器翻译前沿讲习班。他主持了国家自然科学基金面上项目、上海市浦江人才计划和日本国家青年基金。他担任了国际权威会议ICLR/NAACL/CoNLL的机器翻译领域主席，领导的团队在国际权威测评WMT/CoNLL中获得多次第一名。其相关技术被广泛应用在东京奥运会官方机器翻译软件VoiceTra上。