Mark Hopkins

PUBLICATIONS

Patents

  • Mark Hopkins and Jonathan May. Systems and methods for tuning parameters in statistical machine translation. U.S. Patent 8,694,303, issued April 8, 2014.
  • Kevin Knight, Michel Galley, Mark Hopkins, Daniel Marcu, and Ignacio Thayer. Training for a text-to-text application which uses string to tree conversion for training and decoding. U.S. Patent 8,600,728, issued December 3, 2013.

Refereed

  • Zhengyao Gu and Mark Hopkins. On the Evaluation of Neural Selective Prediction Methods for Natural Language Processing. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023. [pdf] [bib]
  • Ananthan Nambiar, Simon Liu, Maeve Heflin, John Malcolm Forsyth, Sergei Maslov, Mark Hopkins, Anna Ritz. Transformer Neural Networks for Protein Family and Interaction Prediction Tasks. In Journal of Computational Biology, 2023. [pdf]
  • Mark Hopkins. Towards More Natural Artificial Languages. In the SIGNLL Conference on Computational Natural Language Learning (CoNLL), 2022. [pdf]
  • Ananthan Nambiar, Maeve Heflin, Simon Liu, Sergei Maslov, Mark Hopkins, Anna Ritz. Transforming the Language of Life: Transformer Neural Networks for Protein Prediction Tasks. In Proceedings of the ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2020. [pdf]
  • Vinay Gopalan and Mark Hopkins. Reed at SemEval-2020 Task 9: Fine-Tuning and Bag-of- Words Approaches to Code-Mixed Sentiment Analysis. In Proceedings of the International Workshop on Semantic Evaluation (SemEval), 2020. [pdf]
  • Mark Hopkins, Ronan Le Bras, Cristian Petrescu-Prahova, Gabriel Stanovsky, Hannaneh Hajishirzi, Rik Koncel-Kedziorski. SemEval 2019 Task 10: Math Question Answering. In Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019).
  • Ananthan Nambiar, Mark Hopkins, and Anna Ritz. Computing the language of life: NLP approaches to feature extraction for protein family classification. In ISMB/ECCB (Late Posters), 2019.
  • Gabriel Stanovsky and Mark Hopkins. Spot the odd man out: Exploring the associative power of lexical resources. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 1533-1542. 2018.
  • Vidur Joshi, Matthew Peters, and Mark Hopkins. Extending a parser to distant domains using a few dozen partially annotated examples. ACL (2018).
  • Mark Hopkins, Cristian Petrescu-Prahova, Roie Levin, Ronan Le Bras, Alvaro Herrasti, and Vidur Joshi. Beyond sentential semantic parsing: Tackling the math SAT with a cascade of tree transducers. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 795-804. 2017.
  • Aaron Sarnat, Vidur Joshi, Cristian Petrescu-Prahova, Alvaro Herrasti, Brandon Stilson, and Mark Hopkins. Interactive visualization for linguistic structure. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 49-54. 2017.
  • Laura Jehl, Adrià de Gispert, Mark Hopkins, and Bill Byrne. Source-side preordering for translation using logistic regression and depth-first branch-and-bound search. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp. 239-248. 2014.
  • Mark Hopkins and Jonathan May. Models of translation competitions. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 1416-1424. 2013.
  • Mark Hopkins and Jonathan May. Tuning as ranking. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1352-1362. Association for Computational Linguistics, 2011.
  • Mark Hopkins, Greg Langmead, and Tai Vo. Extraction programs: a unified approach to translation rule extraction. In Proceedings of the Sixth Workshop on Statistical Machine Translation, pp. 523-532. Association for Computational Linguistics, 2011.
  • Mark Hopkins and Greg Langmead. SCFG decoding without binarization. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 646-655. Association for Computational Linguistics, 2010.
  • Andreas Maletti, Jonathan Graehl, Mark Hopkins and Kevin Knight. The power of extended top-down tree transducers. SIAM J. Comput. 39 (2009): 410-430.
  • Mark Hopkins and Greg Langmead. Cube pruning as heuristic search. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pp. 62-71. 2009.
  • Mark Hopkins and Jonas Kuhn. Machine translation as tree labeling. In Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in Statistical Translation, pp. 41-48. Association for Computational Linguistics, 2007.
  • Mark Hopkins and Jonas Kuhn. Deep grammars in a tree labeling approach to syntax-based statistical machine translation. In Proceedings of the Workshop on Deep Linguistic Processing, pp. 33-40. Association for Computational Linguistics, 2007.
  • Mark Hopkins and Judea Pearl. Causality and counterfactuals in the situation calculus. Journal of Logic and Computation 17, no. 5 (2007): 939-953.
  • Mark Hopkins and Jonas Kuhn. Exploring the potential of intractable parsers. In Proceedings of COLING/ACL, pp. 369-376. Association for Computational Linguistics, 2006.
  • Mark Hopkins and Jonas Kuhn. A framework for incorporating alignment information in parsing. In Proceedings of the International Workshop on Cross-Language Knowledge Induction, pp. 9-16. Association for Computational Linguistics, 2006.
  • Michel Galley, Mark Hopkins, Kevin Knight, and Daniel Marcu. What’s in a translation rule? In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004. 2004.
  • Mark Hopkins and Judea Pearl. Clarifying the usage of structural models for commonsense causal reasoning. In Proceedings of the AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning, pp. 83-89. Menlo Park, CA: AAAI Press, 2003.
  • Mark Hopkins. LAYERWIDTH: Analysis of a new metric for directed acyclic graphs. In Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence, pp. 321-328. Morgan Kaufmann Publishers Inc., 2002.
  • Mark Hopkins. Strategies for determining causes of events. In AAAI/IAAI, pp. 546-552. 2002.
  • Mark Hopkins and Adnan Darwiche. A practical relaxation of constant-Factor treewidth approximation algorithms. In Proceedings of the First European Workshop on Probabilistic Graphical Models, pp. 71-80, 2002.
  • Adnan Darwiche and Mark Hopkins. Using recursive decomposition to construct elimination orders, jointrees, and dtrees. ECSQARU (2001).