| A Bayesian model of diachronic meaning change L Frermann, M Lapata Transactions of the Association for Computational Linguistics 4, 31-45, 2016 | 185 | 2016 |
| Inducing document structure for aspect-based summarization L Frermann, A Klementiev Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 66 | 2019 |
| A hierarchical bayesian model for unsupervised induction of script knowledge L Frermann, I Titov, M Pinkal Proceedings of the 14th Conference of the European Chapter of the …, 2014 | 61 | 2014 |
| Screenplay summarization using latent narrative structure P Papalampidi, F Keller, L Frermann, M Lapata arXiv preprint arXiv:2004.12727, 2020 | 52 | 2020 |
| Evaluating debiasing techniques for intersectional biases S Subramanian, X Han, T Baldwin, T Cohn, L Frermann arXiv preprint arXiv:2109.10441, 2021 | 47 | 2021 |
| Whodunnit? crime drama as a case for natural language understanding L Frermann, SB Cohen, M Lapata Transactions of the Association for Computational Linguistics 6, 1-15, 2018 | 33 | 2018 |
| Fairness-aware class imbalanced learning S Subramanian, A Rahimi, T Baldwin, T Cohn, L Frermann arXiv preprint arXiv:2109.10444, 2021 | 28 | 2021 |
| Contrastive learning for fair representations A Shen, X Han, T Cohn, T Baldwin, L Frermann arXiv preprint arXiv:2109.10645, 2021 | 24 | 2021 |
| Incremental bayesian category learning from natural language L Frermann, M Lapata Cognitive science 40 (6), 1333-1381, 2016 | 20 | 2016 |
| Optimising equal opportunity fairness in model training A Shen, X Han, T Cohn, T Baldwin, L Frermann arXiv preprint arXiv:2205.02393, 2022 | 18 | 2022 |
| Unsupervised induction of linguistic categories with records of reading, speaking, and writing M Barrett, AV González-Garduño, L Frermann, A Søgaard Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 18 | 2018 |
| PPT: Parsimonious parser transfer for unsupervised cross-lingual adaptation K Kurniawan, L Frermann, P Schulz, T Cohn arXiv preprint arXiv:2101.11216, 2021 | 17 | 2021 |
| Does Representational Fairness Imply Empirical Fairness? A Shen, X Han, T Cohn, T Baldwin, L Frermann Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022 …, 2022 | 15 | 2022 |
| Inducing Semantic Micro-Clusters from Deep Multi-View Representations of Novels L Frermann, G Szarvas In Proceedings of the Conference on Empirical Methods on Natural Language …, 2017 | 14 | 2017 |
| Systematic evaluation of predictive fairness X Han, A Shen, T Cohn, T Baldwin, L Frermann arXiv preprint arXiv:2210.08758, 2022 | 10 | 2022 |
| fairlib: A unified framework for assessing and improving classification fairness X Han, A Shen, Y Li, L Frermann, T Baldwin, T Cohn arXiv preprint arXiv:2205.01876, 2022 | 10 | 2022 |
| Fairlib: A unified framework for assessing and improving fairness X Han, A Shen, Y Li, L Frermann, T Baldwin, T Cohn Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 9 | 2022 |
| Extractive NarrativeQA with heuristic pre-training L Frermann Proceedings of the 2nd Workshop on Machine Reading for Question Answering …, 2019 | 9 | 2019 |
| Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing L Frermann, J Li, S Khanehzar, G Mikolajczak The 61st Annual Meeting of the Association for Computational Linguistics 1 …, 2023 | 8 | 2023 |
| Commonsense knowledge in word associations and ConceptNet C Liu, T Cohn, L Frermann arXiv preprint arXiv:2109.09309, 2021 | 8 | 2021 |
Mirella LapataSchool of Informatics, Edinburgh UniversityVerified email at inf.ed.ac.uk