Ekaterina Kochmar
Ekaterina Kochmar
Assistant Professor, Natural Language Processing Department, MBZUAI
Verified email at - Homepage
Cited by
Cited by
Text readability assessment for second language learners
M Xia, E Kochmar, T Briscoe
arXiv preprint arXiv:1906.07580, 2019
Grammatical error correction using hybrid systems and type filtering
M Felice, Z Yuan, ØE Andersen, H Yannakoudakis, E Kochmar
Proceedings of the Eighteenth Conference on Computational Natural Language …, 2014
Classification of twitter accounts into automated agents and human users
Z Gilani, E Kochmar, J Crowcroft
Proceedings of the 2017 IEEE/ACM international conference on advances in …, 2017
CAMB at CWI shared task 2018: Complex word identification with ensemble-based voting
S Gooding, E Kochmar
Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building …, 2018
Identification of a writer’s native language by error analysis
E Kochmar
Master’s thesis, University of Cambridge, 2011
Complex word identification as a sequence labelling task
S Gooding, E Kochmar
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
Automated personalized feedback improves learning gains in an intelligent tutoring system
E Kochmar, DD Vu, R Belfer, V Gupta, IV Serban, J Pineau
Artificial Intelligence in Education: 21st International Conference, AIED …, 2020
Recursive context-aware lexical simplification
S Gooding, E Kochmar
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
Automated data-driven generation of personalized pedagogical interventions in intelligent tutoring systems
E Kochmar, DD Vu, R Belfer, V Gupta, IV Serban, J Pineau
International Journal of Artificial Intelligence in Education 32 (2), 323-349, 2022
A new era: Intelligent tutoring systems will transform online learning for millions
F St-Hilaire, DD Vu, A Frau, N Burns, F Faraji, J Potochny, S Robert, ...
arXiv preprint arXiv:2203.03724, 2022
MTLB-STRUCT@ parseme 2020: Capturing unseen multiword expressions using multi-task learning and pre-trained masked language models
S Taslimipoor, S Bahaadini, E Kochmar
arXiv preprint arXiv:2011.02541, 2020
Detecting learner errors in the choice of content words using compositional distributional semantics
E Kochmar, T Briscoe
Association for Computational Linguistics, 2014
Deep discourse analysis for generating personalized feedback in intelligent tutor systems
M Grenander, R Belfer, E Kochmar, IV Serban, F St-Hilaire, JCK Cheung
Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 15534 …, 2021
How useful are educational questions generated by large language models?
S Elkins, E Kochmar, I Serban, JCK Cheung
International Conference on Artificial Intelligence in Education, 536-542, 2023
Detecting multiword expression type helps lexical complexity assessment
E Kochmar, S Gooding, M Shardlow
arXiv preprint arXiv:2005.05692, 2020
Word complexity is in the eye of the beholder
S Gooding, E Kochmar, SM Yimam, C Biemann
Proceedings of the 2021 Conference of the North American Chapter of the …, 2021
Hoo 2012 error recognition and correction shared task: Cambridge university submission report
E Kochmar, O Andersen, E Briscoe
Association for Computational Linguistics, 2012
Capturing anomalies in the choice of content words in compositional distributional semantic space
E Kochmar, T Briscoe
ACL Home Association for Computational Linguistics, 2013
A large-scale, open-domain, mixed-interface dialogue-based ITS for STEM
IV Serban, V Gupta, E Kochmar, DD Vu, R Belfer, J Pineau, A Courville, ...
Artificial Intelligence in Education: 21st International Conference, AIED …, 2020
‘Calling on the classical phone’: a distributional model of adjective-noun errors in learners’ English
A Herbelot, E Kochmar
Proceedings of COLING 2016, the 26th International Conference on …, 2016
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