swabha swayamdipta

swabha@cs.cmu.edu
185 Stevens Way, Box 352350, Seattle WA
me

I am a PhD student in the Language Technologies Institute at Carnegie Mellon University. My advisors are Noah Smith and Chris Dyer. My research interests are primarily in structured prediction for natural language, with a focus on broad-coverage semantic parsing. In particular, I am interested in exploring new ways of incorporating syntactic cues and structural inductive biases to predict semantic structures for data across multiple domains, genres and languages. In addition to predicting semantic structures for language with high accuracy, I’m also interested in exploring how these structures can be utilized for downstream applications such as question answering.

Since Aug 2015, I have relocated to Seattle, and have been a visiting student at the Paul G. Allen School of Computer Science and Engineering at University of Washington, Seattle. I am currently an intern at the Allen Institute for Artificial Intelligence in Seattle. In the summer of 2017, I interned at Google AI Language in New York.

In 2013, I graduated from a Masters program at Columbia University, where I was advised by Owen Rambow. During this period, I worked on detection of influence and power in online social media.

news

Sep 17 2018: Attended the MSR AI Breakthroughs Workshop.

Aug 30 2018: Talk on Syntactic Scaffolds for Semantic Structures at NW-NLP 2018 now live!

Aug 20 2018: Co-presented the Multilingual FrameNet tutorial at COLING. [Slides and References]

Aug 10 2018: Long paper titled "Syntactic Scaffolds for Semantic Structures" accepted to EMNLP 2018!

Aug 05 2018: Pre-trained models now available for end-to-end frame-semantic parsing using open-sesame on both FN 1.5 and FN 1.7.

publications

  • Syntactic Scaffolds for Semantic Structures.
    Swabha Swayamdipta, Sam Thomson, Kenton Lee, Luke Zettlemoyer, Chris Dyer, Noah A. Smith.
    (To appear) Proceedings of EMNLP 2018. [Talk]
  • Polyglot Semantic Role Labeling.
    Phoebe Mulcaire, Swabha Swayamdipta, Noah A. Smith.
    Proceedings of ACL 2018.
  • Learning Joint Semantic Parsers from Disjoint Data.
    Hao Peng, Sam Thomson, Swabha Swayamdipta, Noah A. Smith.
    Proceedings of NAACL 2018.
  • Annotation Artifacts in Natural Language Inference Data.
    Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, Noah A. Smith.
    Proceedings of NAACL 2018. [Poster]
  • Multi-Mention Learning for Reading Comprehension with Neural Cascades.
    Swabha Swayamdipta, Ankur P. Parikh and Tom Kwaitkowski.
    Proceedings of ICLR 2018. [Poster]
  • Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold.
    Swabha Swayamdipta, Sam Thomson, Chris Dyer and Noah A. Smith.
    arXiv preprint, arXiv:1706.09528 [cs.CL] . [Poster] [Code]
  • Multi-task Learning for Incremental Parsing using Stack LSTMs.
    Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer and Noah A. Smith.
    Workshop for Women in Machine Learning, Neural Information Processing Systems (NIPS 2016). [Poster]
  • Greedy, Joint Syntactic and Semantic Parsing with Stack LSTMs.
    Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer and Noah A. Smith.
    Proceedings of CoNLL 2016. [Code] [Talk]
  • A Dependency Parser for Tweets.
    Lingpeng Kong, Nathan Schneider, Swabha Swayamdipta, Archna Bhatia, Chris Dyer and Noah A. Smith.
    Proceedings of EMNLP 2014.
  • CMU: Arc-Factored, Discriminative Semantic Dependency Parsing.
    Sam Thomson, David Bamman, Jesse Dodge, Swabha Swayamdipta, Nathan Schneider, Chris Dyer and Noah A. Smith.
    Proceedings of SemEval 2014.
  • The CMU Machine Translation Systems.
    Austin Matthews, Chris Dyer, Alon Lavie, Greg Hanneman, Waleed Ammar, Archna Bhatia, Swabha Swayamdipta, Eva Schlinger and Yulia Tsvetkov.
    Workshop on Machine Translation (WMT 2014).
  • The Pursuit of Power and its Manifestation in Written Dialog.
    Swabha Swayamdipta and Owen Rambow.
    IEEE International Conference of Semantic Computing (ICSC 2012).
  • teaching

  • Tutorial at COLING 2018 for Multilingual FrameNet tutorial at COLING. [Slides and References]
  • Guest lecture on Minimum Bayes Risk decoding in CSE 599 D1: Advanced Topics in Natural Language Processing, taught by Waleed Ammar.
  • Guest lecture on Dependency Parsing for CSEP 517: Natural Language Processing, taught by Noah Smith.
  • Guest lecture on Unsupervised Learning for CSE 446 Machine Learning, taught by Noah Smith. [Slides]
  • Lead Teaching Assistant for Undergrad NLP (11-411) taught by Chris Dyer, Alon Lavie and Shomir Wilson, in the Spring of 2015.
  • Guest lecture on Dependency Parsing with the Chu-Liu-Edmonds algorithm for Algorithms for NLP, co-taught with Sam Thomson. [Slides].