Mohammad Taher Pilehvar

Assistant Professor
Taher is an NLP researcher. His research interests mostly lie within lexical semantics with special focus on semantic representation of ambiguous words. Taher has contributed to the field of lexical semantics with several publications (over 20 papers in *ACL venues), including two “best paper award” nominees at ACL 2013 and 2017. Taher has also organized multiple international workshops and has instructed tutorials with hundreds of attendees at top-tier NLP conferences. Taher holds an Affiliated Lectureship position at the Language Technology Lab of the University of Cambridge.

Research Interests

  • Natural Language Processing (NLP)
  • Lexical Semantics
  • Semantic Representation
  • Deep Learning in NLP
  • Research
  • Teaching

Selected Publications

  • V. Prokhorov, M. T. Pilehvar, D. Kartsaklis, P. Lio, and N. Collier
    Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces.
    AAAI 2019, Hawaii, USA.
  • M. T. Pilehvar and J. Camacho-Collados
    WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations.
    NAACL 2019, Minneapolis, USA.
  • M. T. Pilehvar
    On the Importance of Distinguishing Word Meaning Representations: A Case Study on Reverse Dictionary Mapping.
    NAACL 2019, Minneapolis, USA.
  • V. Prokhorov, M. T. Pilehvar, and N. Collier
    Generating Knowledge Graph Paths from Textual Definitions using Sequence-to-Sequence Models.
    NAACL 2019, Minneapolis, USA.
  • M. T. Pilehvar, D. Kartsaklis, V. Prokhorov and N. Collier
    Card-660: Cambridge Rare Word Dataset – a Reliable Benchmark for Infrequent Word Representation Models.
    EMNLP 2018, Brussels, Belgium.
  • D. Kartsaklis, M. T. Pilehvar and N. Collier
    Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs.
    EMNLP 2018, Brussels, Belgium.
  • H. Le, D. Can, S. T. Vu, T. H. Dang, M. T. Pilehvar and N. Collier
    Large-scale Exploration of Neural Relation Classification Architectures.
    EMNLP 2018, Brussels, Belgium.
  • M. Gritta, M. T. Pilehvar, and N. Collier
    Which Melbourne? Augmenting Geocoding with Maps.
    ACL 2018, Melbourne, Australia.
  • J. Camacho-Collados and M. T. Pilehvar
    From Word to Sense Embeddings: A Survey on Vector Representations of Meaning.
    Journal of Artificial Intelligence Research, 2018.

See more [here]

  • Artificial Intelligence (undergraduate – Iran University of Science and Technology): 971, 972, 981
  • Deep Learning (undergraduate – Iran University of Science and Technology): 981
  • Natural Language Processing (graduate – Iran University of Science and Technology): 981
  • Applied Deep Learning (graduate – Iran University of Science and Technology): 972
  • Computational Linguistics (Graduate – University of Cambridge), seminars series, 2017-2
  • Computational Linguistics (Graduate – University of Cambridge), seminars series, 2015-2
  • Word Vector Space Specialisation (Tutorial – EACL 2017, Valencia)
  • Semantic Representation of Word Senses and Concepts (Tutorial – ACL 2016, Berlin)
  • Semantic Similarity (Tutorial – EMNLP 2015, Lisbon)
  • Embeddings in Natural Language Processing (Tutorial – COLING, Barcelona), to take place on Summer 2020
  • Embeddings in Natural Language Processing (one-week course @ ESSLLI), to take place on Summer 2020