前往小程序,Get更优阅读体验!
立即前往
首页
学习
活动
专区
工具
TVP
发布
社区首页 >专栏 >【犀牛鸟学问】ACL2017论文报告会

【犀牛鸟学问】ACL2017论文报告会

作者头像
腾讯高校合作
发布2018-03-21 14:46:18
5680
发布2018-03-21 14:46:18
举报
文章被收录于专栏:腾讯高校合作腾讯高校合作

近日,自然语言处理领域国际最权威的学术会议ACL 2017公布了录用论文。为了促进国内自然语言处理相关研究的发展以及研究者之间的交流,中国中文信息学会青年工作委员会联合腾讯公司将于2017年4月22日在北京市知春路希格玛大厦举办“ACL 2017论文报告会”。我们邀请国内部分被录用论文的作者报告其论文方法,共同探讨自然语言处理领域的新发展和新技术,期待您的光临!

时间:2017年4月22日

地点:北京市海淀区知春路49号希格玛大厦地下一层小剧场

主办方:中国中文信息学会青年工作委员会、腾讯高校合作

报名链接:请点击文末左下角“阅读原文”

报名截止时间:2017年4月21日09:00

日程

8:45-9:00 (Open Remarks) 9:00-10:48 (Oral Session 1: Machine Translation) 9:00-9:18 Prior Knowledge Integration for Neural Machine Translation using Posterior Regularization Authors: Jiacheng Zhang, Yang Liu, Huanbo Luan, Jingfang Xu and Maosong Sun 9:18-9:36 Visualizing and Understanding Neural Machine Translation Authors: Yanzhuo Ding, Yang Liu, Huanbo Luan and Maosong Sun 9:36-9:54 Incorporating Word Reordering Knowledge into Attention-based Neural Machine Translation Authors: Jinchao Zhang, Mingxuan Wang, Qun Liu and Jie Zhou 9:54-10:12 Modeling Source Syntax for Neural Machine Translation Authors: Junhui Li, Deyi Xiong, Zhaopeng Tu, Muhua Zhu and Guodong Zhou 10:12-9:30 Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder Authors: Huadong Chen, Shujian Huang, David Chiang and Jiajun Chen 10:30-10:48 Sequence-to-Dependency Neural Machine Translation Authors: Shuangzhi Wu, Dongdong Zhang, Nan Yang, Mu Li and Ming Zhou 10:48-11:18 (Coffee Break and Poster) 11:18-12:30

(Oral Session 2: Parsing/Semantic/Discourse) 11:18-11:36 Parsing to 1-endpoint-crossing, pagenumber-2 graphs Authors: Junjie Cao, Sheng Huang, Weiwei Sun, Xiaojun Wan 11:36-11:54 A Progressive Learning Approach to Chinese SRL Using Heterogeneous Data Authors: Qiaolin Xia, Zhifang Sui and Baobao Chang 11:54-12:12 Discourse Mode Identification in Essays Authors: Wei Song, Dong Wang, Ruiji Fu, Lizhen Liu, Ting Liu, Guoping Hu 12:12-12:30 Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution Authors: Ting Liu, Yiming Cui, Qingyu Yin, Wei-Nan Zhang, Shijin Wang and Guoping Hu 12:30-14:00 (Lunch) 14:00-15:30

(Oral Session 3: Sentiment/Information Extraction) 14:00-14:18 Linguistically Regularized LSTM for Sentiment Classification Authors: Qiao Qian, Minlie Huang and xiaoyan zhu 14:18-14:36 Prerequisite Relation Learning for Concepts in MOOCs Authors: Liangming Pan, Chengjiang Li, Juanzi Li and Jie Tang 14:36-14:54 Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix Authors: Bingfeng Luo, Yansong Feng, Zheng Wang, Zhanxing Zhu, Songfang Huang, Rui Yan and Dongyan Zhao 14:54-15:12 Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme Authors: Suncong Zheng, Feng Wang and Hongyun Bao 15:12-15:30 Automatically Labeled Data Generation for Large Scale Event Extraction Authors: Yubo Chen, Kang Liu and Jun Zhao 15:30-16:00 (Coffee Break and Poster) 16:00-17:30

(Oral Session 4: Social Media/Word Segmentatin/Question Answering) 16:00-16:18 CANE: Context-Aware Network Embedding for Relation Modeling Authors: Cunchao Tu, Han Liu, Zhiyuan Liu and Maosong Sun 16:18-16:36 Adversarial Multi-Criteria Learning for Chinese Word Segmentation Authors: Xinchi Chen, Zhan Shi, Xipeng Qiu and Xuanjing Huang 16:36-16:54 Generating Natural Answer by Incorporating Copying and Retrieving Mechanisms in Sequence-to-Sequence Learning Authors: Shizhu He, Kang Liu and Jun Zhao 16:54-17:12 Attention-over-Attention Neural Networks for Reading Comprehension Authors: Yiming Cui, Zhipeng Chen, si wei, Shijin Wang, Ting Liu and Guoping Hu 17:12-17:30 Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots Authors: Yu Wu, Wei Wu, Chen Xing, Ming Zhou and Zhoujun Li 17:30-17:40 (Closing Remarks)

本文参与 腾讯云自媒体分享计划,分享自微信公众号。
原始发表:2017-04-14,如有侵权请联系 cloudcommunity@tencent.com 删除

本文分享自 腾讯高校合作 微信公众号,前往查看

如有侵权,请联系 cloudcommunity@tencent.com 删除。

本文参与 腾讯云自媒体分享计划  ,欢迎热爱写作的你一起参与!

评论
登录后参与评论
0 条评论
热度
最新
推荐阅读
相关产品与服务
NLP 服务
NLP 服务(Natural Language Process,NLP)深度整合了腾讯内部的 NLP 技术,提供多项智能文本处理和文本生成能力,包括词法分析、相似词召回、词相似度、句子相似度、文本润色、句子纠错、文本补全、句子生成等。满足各行业的文本智能需求。
领券
问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档