Department of Computer Science

Machine Learning Research Group

University of Texas at Austin Artificial Intelligence Lab

Publications: 2016


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  1. Stacking With Auxiliary Features for Combining Supervised and Unsupervised Ensembles
    [Details] [PDF]
    Nazneen Fatema Rajani and Raymond J. Mooney
    In Proceedings of the Ninth Text Analysis Conference (TAC 2016), 2016.
  2. Stacking With Auxiliary Features: Improved Ensembling for Natural Language and Vision
    [Details] [PDF] [Slides (PDF)]
    Nazneen Fatema Rajani
    November 2016. PhD proposal, Department of Computer Science, The University of Texas at Austin.
  3. An Analysis of Using Semantic Parsing for Speech Recognition
    [Details] [PDF] [Slides (PPT)]
    Rodolfo Corona
    2016. Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
  4. Continuously Improving Natural Language Understanding for Robotic Systems through Semantic Parsing, Dialog, and Multi-modal Perception
    [Details] [PDF]
    Jesse Thomason
    November 2016. PhD proposal, Department of Computer Science, The University of Texas at Austin.
  5. Natural Language Semantics Using Probabilistic Logic
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
    I. Beltagy
    PhD Thesis, Department of Computer Science, The University of Texas at Austin, December 2016.
  6. Statistical Script Learning with Recurrent Neural Networks
    [Details] [PDF] [Poster]
    Karl Pichotta and Raymond J. Mooney
    In Proceedings of the Workshop on Uphill Battles in Language Processing (UBLP) at EMNLP 2016, Austin, TX, November 2016.
  7. PIC a Different Word: A Simple Model for Lexical Substitution in Context
    [Details] [PDF]
    Stephen Roller and Katrin Erk
    In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), 1121-1126, San Diego, California, 2016.
  8. MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification
    [Details] [PDF]
    Ye Zhang and Stephen Roller and Byron Wallace.
    In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), 1522--1527, San Diego, California, 2016.
  9. Stacking With Auxiliary Features
    [Details] [PDF]
    Nazneen Fatema Rajani and Raymond J. Mooney
    ArXiv preprint arXiv:1605.08764, 2016.
  10. Improved Semantic Parsers For If-Then Statements
    [Details] [PDF]
    I. Beltagy and Chris Quirk
    To Appear In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), Berlin, Germany, 2016.
  11. Combining Supervised and Unsupervised Ensembles for Knowledge Base Population
    [Details] [PDF]
    Nazneen Fatema Rajani and Raymond J. Mooney
    To Appear In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16), 2016.
  12. Using Sentence-Level LSTM Language Models for Script Inference
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
    Karl Pichotta and Raymond J. Mooney
    In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), 279--289, Berlin, Germany, 2016.
  13. Learning Multi-Modal Grounded Linguistic Semantics by Playing "I Spy"
    [Details] [PDF]
    Jesse Thomason and Jivko Sinapov and Maxwell Svetlik and Peter Stone and Raymond J. Mooney
    In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), 3477--3483, New York City, 2016.
  14. Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text
    [Details] [PDF] [Poster]
    Subhashini Venugopalan and Lisa Anne Hendricks and Raymond Mooney and Kate Saenko
    In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16), 1961--1966, Austin, Texas, 2016.
  15. Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
    [Details] [PDF]
    Lisa Anne Hendricks and Subhashini Venugopalan and Marcus Rohrbach and Raymond Mooney and Kate Saenko and Trevor Darrell
    In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR-16), 1--10, 2016.
  16. Learning Statistical Scripts with LSTM Recurrent Neural Networks
    [Details] [PDF] [Slides (PPT)] [Slides (PDF)]
    Karl Pichotta and Raymond J. Mooney
    In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, February 2016.
  17. Representing Meaning with a Combination of Logical and Distributional Models
    [Details] [PDF]
    I. Beltagy and Stephen Roller and Pengxiang Cheng and Katrin Erk and Raymond J. Mooney
    The special issue of Computational Linguistics on Formal Distributional Semantics, 42(4), 2016.