| Blackbox meets blackbox: Representational similarity and stability analysis of neural language models and brains S Abnar, L Beinborn, R Choenni, W Zuidema arXiv preprint arXiv:1906.01539, 2019 | 86 | 2019 |
| Predicting the difficulty of language proficiency tests L Beinborn, T Zesch, I Gurevych Transactions of the Association for Computational Linguistics 2, 517-530, 2014 | 70 | 2014 |
| Cognate production using character-based machine translation L Beinborn, T Zesch, I Gurevych Proceedings of the sixth international joint conference on natural language …, 2013 | 59 | 2013 |
| Multilingual language models predict human reading behavior N Hollenstein, F Pirovano, C Zhang, L Jäger, L Beinborn arXiv preprint arXiv:2104.05433, 2021 | 49 | 2021 |
| Semantic drift in multilingual representations L Beinborn, R Choenni Computational Linguistics 46 (3), 571-603, 2020 | 35 | 2020 |
| Multimodal grounding for language processing L Beinborn, T Botschen, I Gurevych arXiv preprint arXiv:1806.06371, 2018 | 35 | 2018 |
| Relative importance in sentence processing N Hollenstein, L Beinborn arXiv preprint arXiv:2106.03471, 2021 | 34 | 2021 |
| Readability for foreign language learning: The importance of cognates L Beinborn, T Zesch, I Gurevych ITL-International Journal of Applied Linguistics 165 (2), 136-162, 2014 | 32 | 2014 |
| Generating image descriptions via sequential cross-modal alignment guided by human gaze E Takmaz, S Pezzelle, L Beinborn, R Fernández arXiv preprint arXiv:2011.04592, 2020 | 31 | 2020 |
| Towards best practices for leveraging human language processing signals for natural language processing N Hollenstein, M Barrett, L Beinborn Proceedings of the second workshop on linguistic and neurocognitive …, 2020 | 29 | 2020 |
| Predicting and manipulating the difficulty of text-completion exercises for language learning LM Beinborn Technische Universität Darmstadt, 2016 | 28 | 2016 |
| Candidate evaluation strategies for improved difficulty prediction of language tests L Beinborn, T Zesch, I Gurevych Proceedings of the Tenth Workshop on Innovative Use of NLP for Building …, 2015 | 28 | 2015 |
| Robust evaluation of language–brain encoding experiments L Beinborn, S Abnar, R Choenni International conference on computational linguistics and intelligent text …, 2019 | 23 | 2019 |
| Probing multilingual BERT for genetic and typological signals T Rama, L Beinborn, S Eger arXiv preprint arXiv:2011.02070, 2020 | 19 | 2020 |
| Towards fine-grained readability measures for self-directed language learning L Beinborn, T Zesch, I Gurevych Electronic Conference Proceedings 80, 11-19, 2012 | 19 | 2012 |
| Predicting the spelling difficulty of words for language learners L Beinborn, T Zesch, I Gurevych proceedings of the 11th Workshop on Innovative Use of NLP for Building …, 2016 | 15 | 2016 |
| Analyzing cognitive plausibility of subword tokenization L Beinborn, Y Pinter arXiv preprint arXiv:2310.13348, 2023 | 13 | 2023 |
| Cognitive plausibility in natural language processing L Beinborn, N Hollenstein Springer, 2024 | 11 | 2024 |
| Patterns of text readability in human and predicted eye movements N Hollenstein, I Gonzalez-Dios, L Beinborn, L Jäger Proceedings of the Workshop on Cognitive Aspects of the Lexicon, 1-15, 2022 | 10 | 2022 |
| A cross-lingual comparison of human and model relative word importance F Morger, S Brandl, L Beinborn, N Hollenstein Proceedings of the 2022 CLASP Conference on (Dis) embodiment, 11-23, 2022 | 8 | 2022 |
Iryna GurevychFull Professor, TU Darmstadt; Adjunct Professor, MBZUAI, UAE; Affiliated Professor, INSAIT, BulgariaVerified email at cs.tu-darmstadt.de
