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cs.CL 方向,今日共计25篇
[cs.CL]:
【1】 Towards Debiasing Fact Verification Models
标题:面向消除偏差的事实验证模型
作者: Tal Schuster, Regina Barzilay
备注:EMNLP 2019
链接:https://arxiv.org/abs/1908.05267
【2】 The lexical and grammatical sources of neg-raising inferences
标题:否定提升推理的词汇和语法来源
作者: Hannah Youngeun An, Aaron Steven White
链接:https://arxiv.org/abs/1908.05253
【3】 On The Evaluation of Machine Translation Systems Trained With Back-Translation
标题:关于回译训练的机器翻译系统的评估
作者: Sergey Edunov, Michael Auli
链接:https://arxiv.org/abs/1908.05204
【4】 SG-Net: Syntax-Guided Machine Reading Comprehension
标题:SG-NET:语法制导的机器阅读理解
作者: Zhuosheng Zhang, Hai Zhao
链接:https://arxiv.org/abs/1908.05147
【5】 MemeFaceGenerator: Adversarial Synthesis of Chinese Meme-face from Natural Sentences
标题:MemeFaceGenerator:基于自然句子的汉语Meme-face对抗性合成
作者: Yifu Chen, Baoxun Wang
链接:https://arxiv.org/abs/1908.05138
【6】 Mastering emergent language: learning to guide in simulated navigation
标题:掌握紧急语言:在模拟导航中学习引导
作者: Mathijs Mul, Elia Bruni
链接:https://arxiv.org/abs/1908.05135
【7】 FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension
标题:FlowDelta:会话机器理解推理中的流信息获取模型
作者: Yi-Ting Yeh, Yun-Nung Chen
备注:Accepted by 1st Workshop NLP for Conversational AI, ACL 2019 Workshop (Cross-submission)
链接:https://arxiv.org/abs/1908.05117
【8】 X-WikiRE: A Large, Multilingual Resource for Relation Extraction asMachine Comprehension
标题:X-WikiRE:一个用于机器理解的关系抽取的大型多语言资源
作者: Mostafa Abdou, Anders Søgaard
链接:https://arxiv.org/abs/1908.05111
【9】 Towards Optimisation of Collaborative Question Answering over Knowledge Graphs
标题:面向知识图的协同问答优化
作者: Kuldeep Singh, Jens Lehmann
链接:https://arxiv.org/abs/1908.05098
【10】 Reactive Multi-Stage Feature Fusion for Multimodal Dialogue Modeling
标题:用于多模态对话建模的反应式多阶段特征融合
作者: Yi-Ting Yeh, Yun-Nung Chen
备注:Accepted for a poster session at the DSTC7 workshop at AAAI 2019
链接:https://arxiv.org/abs/1908.05067
【11】 Fusion of Detected Objects in Text for Visual Question Answering
标题:用于视觉问答的文本中检测对象的融合
作者: Chris Alberti, David Reitter
链接:https://arxiv.org/abs/1908.05054
【12】 FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity Recognition
标题:Flexner:用于命名实体识别的灵活LSTM-CNN堆栈框架
作者: Hongyin Zhu, Yi Zeng
链接:https://arxiv.org/abs/1908.05009
【13】 Establishing Strong Baselines for the New Decade: Sequence Tagging, Syntactic and Semantic Parsing with BERT
标题:为新的十年建立强有力的基线:使用BERT进行序列标记、句法和语义分析
作者: Han He, Jinho D. Choi
链接:https://arxiv.org/abs/1908.04943
【14】 Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation
标题:基于强化学习的自然问题生成的图-序模型
作者: Yu Chen, Mohammed J. Zaki
链接:https://arxiv.org/abs/1908.04942
【15】 Reasoning-Driven Question-Answering for Natural Language Understanding
标题:推理驱动的自然语言理解问答
作者: Daniel Khashabi
链接:https://arxiv.org/abs/1908.04926
【16】 Architecture and evolution of semantic networks in mathematics texts
标题:数学文本中语义网络的结构与演化
作者: Nicolas H. Christianson, Danielle S. Bassett
链接:https://arxiv.org/abs/1908.04911
【17】 Aspect and Opinion Terms Extraction Using Double Embeddings and Attention Mechanism for Indonesian Hotel Reviews
标题:印尼酒店评论中基于双重嵌入和关注机制的方面和观点术语抽取
作者: Jordhy Fernando, Ali Akbar Septiandri
链接:https://arxiv.org/abs/1908.04899
【18】 HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion
标题:HyperKG:用于知识库完成的双曲知识图嵌入
作者: Prodromos Kolyvakis, Dimitris Kiritsis
链接:https://arxiv.org/abs/1908.04895
【19】 Meta Reasoning over Knowledge Graphs
标题:知识图上的元推理
作者: Hong Wang, William Yang Wang
链接:https://arxiv.org/abs/1908.04877
【20】 Entertaining and Opinionated but Too Controlling: A Large-Scale User Study of an Open Domain Alexa Prize System
标题:娱乐性和固执己见但过于控制:一个开放领域Alexa奖系统的大规模用户研究
作者: Kevin K. Bowden, Marilyn Walker
备注:To appear in 1st International Conference on Conversational User Interfaces (CUI 2019)
链接:https://arxiv.org/abs/1908.04832
【21】 Domain Adaptive Training BERT for Response Selection
标题:用于响应选择的域自适应训练BERT
作者: Taesun Whang, HeuiSeok Lim
链接:https://arxiv.org/abs/1908.04812
【22】 Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding
标题:基于提取语句嵌入的可伸缩注意句对建模
作者: Oren Barkan, Noam Koenigstein
链接:https://arxiv.org/abs/1908.05161
【23】 VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering
标题:VideoNavQA:弥合可视和具体化问答之间的差距
作者: Cătălina Cangea, Aaron Courville
备注:To appear at BMVC 2019. 15 pages, 5 figures
链接:https://arxiv.org/abs/1908.04950
【24】 Towards Diverse and Accurate Image Captions via Reinforcing Determinantal Point Process
标题:通过强化判定点过程实现图像字幕的多样化和精确化
作者: Qingzhong Wang, Antoni B. Chan
链接:https://arxiv.org/abs/1908.04919
【25】 A Cascade Sequence-to-Sequence Model for Chinese Mandarin Lip Reading
标题:汉语普通话唇读的级联序列到序列模型
作者: Ya Zhao, Mingli Song
链接:https://arxiv.org/abs/1908.04917
翻译:腾讯翻译君
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