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Cambridge Language Sciences

Interdisciplinary Research Centre
 
Read more at: Dr Karen Ottewell MCIL

Dr Karen Ottewell MCIL

Assessment of academic English; the "cultural" impact on writing; academic writing across the disciplines; achieving clarity in writing; academic literacy

Theses / dissertations

2021

  • Ottewell, K., 2021. Looking behind the Writing: The design and implementation of a framework to provide transitional support for the development of written articulacy at PG level – a University of Cambridge Case Study

  • Read more at: Dr Helen Yannakoudakis

    Dr Helen Yannakoudakis

    Automated assessment

    Conference proceedings

    2019 (No publication date)

  • Farag, Y., Yannakoudakis, H. and Briscoe, T., 2019 (No publication date). Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input Proceedings of NAACL-HLT 2018, New Orleans, Louisiana, pages 263–271, v. Volume 1
    Doi: http://doi.org/10.18653/v1/N18-1024
  • Mishra, P., Giannakoudaki, E. and Shutova, E., 2019 (No publication date). Neural Character-based Composition Models for Abuse Detection
  • Pushkar, M., Del Tredici, M., Giannakoudaki, E. and Shutova, E., 2019 (No publication date). Author Profiling for Abuse Detection
  • Flachs, S., Lacroix, O., Rei, M., Giannakoudaki, E. and Søgaard, A., 2019 (No publication date). A Simple and Robust Approach to Detecting Subject-Verb Agreement Errors.
  • 2019 (Accepted for publication)

  • Mu, J., Giannakoudaki, E. and Shutova, E., 2019 (Accepted for publication). Learning Outside the Box: Discourse-level Features Improve Metaphor Identification. In Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics.,
  • 2019

  • Aglionby, G., Davis, C., Mishra, P., Caines, A., Yannakoudakis, H., Rei, M., Shutova, E. and Buttery, P., 2019. CAMsterdam at SemEval-2019 task 6: Neural and graph-based feature extraction for the identification of offensive tweets NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop,
  • Mishra, P., Del Tredici, M., Giannakoudaki, E. and Shutova, E., 2019. Abusive Language Detection with Graph Convolutional Networks Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, v. 1
    Doi: http://doi.org/10.18653/v1/N19-1221
  • Farag, Y. and Giannakoudaki, E., 2019. Multi-Task Learning for Coherence Modeling. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.,
  • 2017

  • Rei, M. and Giannakoudaki, E., 2017. Auxiliary Objectives for Neural Error Detection Models
  • Giannakoudaki, E., Rei, M., Andersen, OE. and Yuan, Z., 2017. Neural Sequence-Labelling Models for Grammatical Error Correction Proceedings of the 2017 Conference on Empirical Methods in natural Language Processing, v. D17-1
    Doi: http://doi.org/10.18653/v1/D17-1297
  • Shutova, E., Wundsam, A. and Yannakoudakis, H., 2017. Semantic frames and visual scenes: Learning semantic role inventories from image and video descriptions *SEM 2017 - 6th Joint Conference on Lexical and Computational Semantics, Proceedings,
    Doi: http://doi.org/10.18653/v1/s17-1018
  • 2016

  • Alikaniotis, D., Yannakoudakis, H. and Rei, M., 2016. Automatic text scoring using neural networks 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers, v. 2
    Doi: http://doi.org/10.18653/v1/p16-1068
  • Rei, M. and Yannakoudakis, H., 2016. Compositional sequence labeling models for error detection in learner writing 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers, v. 2
  • 2014

  • Felice, M., Yuan, Z., Andersen, ØE., Yannakoudakis, H. and Kochmar, E., 2014. Grammatical error correction using hybrid systems and type filtering CoNLL 2014 - 18th Conference on Computational Natural Language Learning, Proceedings of the Shared Task,
    Doi: http://doi.org/10.3115/v1/w14-1702
  • Journal articles

    2018

  • Yannakoudakis, H., Andersen, ØE., Geranpayeh, A., Briscoe, T. and Nicholls, D., 2018. Developing an automated writing placement system for ESL learners Applied Measurement in Education, v. 31
    Doi: http://doi.org/10.1080/08957347.2018.1464447
  • Other publications

    2018

  • Farag, Y., Yannakoudakis, H. and Briscoe, T., 2018. Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input. CoRR, v. abs/1804.06898

  • Read more at: Dr Angeliki Salamoura

    Dr Angeliki Salamoura

    Second language learning with reference to L2 English; language assessment; learner corpora; bilingualism


    What we do

    Cambridge Language Sciences is an Interdisciplinary Research Centre at the University of Cambridge. Our virtual network connects researchers from five schools across the university as well as other world-leading research institutions. Our aim is to strengthen research collaborations and knowledge transfer across disciplines in order to address large-scale multi-disciplinary research challenges relating to language research.

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