| Modeling language learning using specialized Elo rating J Hou, K Maximilian, JMH Quecedo, N Stoyanova, R Yangarber Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building …, 2019 | 21 | 2019 |
| Applying gamification incentives in the Revita language-learning system J Hou, I Kylliäinen, A Katinskaia, G Furlan, R Yangarber Proceedings of the 9th Workshop on Games and Natural Language Processing …, 2022 | 5 | 2022 |
| Semi-automatically annotated learner corpus for Russian A Katinskaia, M Lebedeva, J Hou, R Yangarber Proceedings of the Thirteenth Language Resources and Evaluation Conference …, 2022 | 5 | 2022 |
| Projecting named entity recognizers without annotated or parallel corpora J Hou, M Koppatz, JMH Quecedo, R Yangarber Nordic Conference on Computational Linguistics, 232-241, 2019 | 4 | 2019 |
| Integration of computer-aided language learning into formal university-level l2 instruction N Stoyanova, J Hou, R Yangarber, M Kopotev L'Analisi Linguistica e Letteraria 29 (3), 2021 | 3 | 2021 |
| What do Transformers Know about Government? J Hou, A Katinskaia, L Kotilainen, S Trangcasanchai, AD Vu, R Yangarber arXiv preprint arXiv:2404.14270, 2024 | | 2024 |
| Effects of sub-word segmentation on performance of transformer language models J Hou, A Katinskaia, AD Vu, R Yangarber arXiv preprint arXiv:2305.05480, 2023 | | 2023 |
| Linguistic Constructs Represent the Domain Model in Intelligent Language Tutoring A Katinskaia, J Hou, AD Vu, R Yangarber Proceedings of the 17th Conference of the European Chapter of the …, 2023 | | 2023 |
| Projecting named entity recognizers from resource-rich to resource-poor languages without annotated or parallel corpora J Hou University of Helsinki, 2020 | | 2020 |
