<?xml version="1.0" encoding="UTF-8" ?>
<volume id="W16">
  <paper id="5900">
    <title>Proceedings of the Workshop on Structured Prediction for NLP</title>
    <editor>Kai-Wei Chang</editor>
    <editor>Ming-Wei Chang</editor>
    <editor>Alexander Rush</editor>
    <editor>Vivek Srikumar</editor>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <url>http://aclweb.org/anthology/W16-59</url>
    <bibtype>book</bibtype>
    <bibkey>SPNLP:2016</bibkey>
  </paper>

  <paper id="5901">
    <title>Inside-Outside and Forward-Backward Algorithms Are Just Backprop (tutorial paper)</title>
    <author><first>Jason</first><last>Eisner</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>1&#8211;17</pages>
    <url>http://aclweb.org/anthology/W16-5901</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>eisner:2016:SPNLP</bibkey>
  </paper>

  <paper id="5902">
    <title>Research on attention memory networks as a model for learning natural language inference</title>
    <author><first>zhuang</first><last>liu</last></author>
    <author><first>Degen</first><last>Huang</last></author>
    <author><first>jing</first><last>zhang</last></author>
    <author><first>kaiyu</first><last>huang</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>18&#8211;24</pages>
    <url>http://aclweb.org/anthology/W16-5902</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>liu-EtAl:2016:SPNLP</bibkey>
  </paper>

  <paper id="5903">
    <title>A Joint Model of Rhetorical Discourse Structure and Summarization</title>
    <author><first>Naman</first><last>Goyal</last></author>
    <author><first>Jacob</first><last>Eisenstein</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>25&#8211;34</pages>
    <url>http://aclweb.org/anthology/W16-5903</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>goyal-eisenstein:2016:SPNLP</bibkey>
  </paper>

  <paper id="5904">
    <title>Posterior regularization for Joint Modeling of Multiple Structured Prediction Tasks with Soft Constraints</title>
    <author><first>Kartik</first><last>Goyal</last></author>
    <author><first>Chris</first><last>Dyer</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>35&#8211;43</pages>
    <url>http://aclweb.org/anthology/W16-5904</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>goyal-dyer:2016:SPNLP</bibkey>
  </paper>

  <paper id="5905">
    <title>A Study of Imitation Learning Methods for Semantic Role Labeling</title>
    <author><first>Travis</first><last>Wolfe</last></author>
    <author><first>Mark</first><last>Dredze</last></author>
    <author><first>Benjamin</first><last>Van Durme</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>44&#8211;53</pages>
    <url>http://aclweb.org/anthology/W16-5905</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>wolfe-dredze-vandurme:2016:SPNLP</bibkey>
  </paper>

  <paper id="5906">
    <title>Introducing DRAIL &#8211; a Step Towards Declarative Deep Relational Learning</title>
    <author><first>Xiao</first><last>Zhang</last></author>
    <author><first>Mar&#237;a Leonor</first><last>Pacheco</last></author>
    <author><first>Chang</first><last>Li</last></author>
    <author><first>Dan</first><last>Goldwasser</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>54&#8211;62</pages>
    <url>http://aclweb.org/anthology/W16-5906</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>zhang-EtAl:2016:SPNLP</bibkey>
  </paper>

  <paper id="5907">
    <title>Unsupervised Neural Hidden Markov Models</title>
    <author><first>Ke M.</first><last>Tran</last></author>
    <author><first>Yonatan</first><last>Bisk</last></author>
    <author><first>Ashish</first><last>Vaswani</last></author>
    <author><first>Daniel</first><last>Marcu</last></author>
    <author><first>Kevin</first><last>Knight</last></author>
    <booktitle>Proceedings of the Workshop on Structured Prediction for NLP</booktitle>
    <month>November</month>
    <year>2016</year>
    <address>Austin, TX</address>
    <publisher>Association for Computational Linguistics</publisher>
    <pages>63&#8211;71</pages>
    <url>http://aclweb.org/anthology/W16-5907</url>
    <bibtype>inproceedings</bibtype>
    <bibkey>tran-EtAl:2016:SPNLP</bibkey>
  </paper>

</volume>

