| A hierarchical recurrent encoder-decoder for generative context-aware query suggestion A Sordoni, Y Bengio, H Vahabi, C Lioma, J Grue Simonsen, JY Nie Proceedings of the 24th ACM International on Conference on Information and …, 2015 | 604 | 2015 |
| MultiFC: A real-world multi-domain dataset for evidence-based fact checking of claims I Augenstein, C Lioma, D Wang, LC Lima, C Hansen, C Hansen, ... arXiv preprint arXiv:1909.03242, 2019 | 254 | 2019 |
| Graph-based term weighting for information retrieval R Blanco, C Lioma Information retrieval 15, 54-92, 2012 | 242 | 2012 |
| A diagnostic study of explainability techniques for text classification P Atanasova Accountable and Explainable Methods for Complex Reasoning over Text, 155-187, 2024 | 218 | 2024 |
| Generating fact checking explanations P Atanasova Accountable and Explainable Methods for Complex Reasoning over Text, 83-103, 2024 | 196 | 2024 |
| Research directions in terrier: a search engine for advanced retrieval on the web I Ounis, C Lioma, C Macdonald, V Plachouras CEPIS Upgrade Journal 8 (1), 2007 | 140 | 2007 |
| On position embeddings in bert B Wang, L Shang, C Lioma, X Jiang, H Yang, Q Liu, JG Simonsen International Conference on Learning Representations, 2020 | 138 | 2020 |
| Encoding word order in complex embeddings B Wang, D Zhao, C Lioma, Q Li, P Zhang, JG Simonsen arXiv preprint arXiv:1912.12333, 2019 | 126 | 2019 |
| FindZebra: a search engine for rare diseases R Dragusin, P Petcu, C Lioma, B Larsen, HL Jørgensen, IJ Cox, ... International journal of medical informatics 82 (6), 528-538, 2013 | 102 | 2013 |
| Quantum-inspired multimodal fusion for video sentiment analysis Q Li, D Gkoumas, C Lioma, M Melucci Information Fusion 65, 58-71, 2021 | 100 | 2021 |
| Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ... Scientific reports 11 (1), 3246, 2021 | 85 | 2021 |
| University of Glasgow at TREC 2006: Experiments in Terabyte and Enterprise Tracks with Terrier. C Lioma, C Macdonald, V Plachouras, J Peng, B He, I Ounis TREC, 2006 | 80 | 2006 |
| What makes the difference? An empirical comparison of fusion strategies for multimodal language analysis D Gkoumas, Q Li, C Lioma, Y Yu, D Song Information Fusion 66, 184-197, 2021 | 78 | 2021 |
| University of Glasgow at WebCLEF 2005: Experiments in per-field normalisation and language specific stemming C Macdonald, V Plachouras, B He, C Lioma, I Ounis Accessing Multilingual Information Repositories: 6th Workshop of the Cross …, 2006 | 59 | 2006 |
| Neural check-worthiness ranking with weak supervision: Finding sentences for fact-checking C Hansen, C Hansen, S Alstrup, J Grue Simonsen, C Lioma Companion proceedings of the 2019 world wide web conference, 994-1000, 2019 | 55 | 2019 |
| Power law distributions in information retrieval C Petersen, JG Simonsen, C Lioma ACM Transactions on Information Systems (TOIS) 34 (2), 1-37, 2016 | 54 | 2016 |
| Part of speech based term weighting for information retrieval C Lioma, R Blanco European Conference on Information Retrieval, 412-423, 2009 | 49 | 2009 |
| Random walk term weighting for information retrieval R Blanco, C Lioma Proceedings of the 30th annual international ACM SIGIR conference on …, 2007 | 49 | 2007 |
| Neural speed reading with structural-jump-lstm C Hansen, C Hansen, S Alstrup, JG Simonsen, C Lioma arXiv preprint arXiv:1904.00761, 2019 | 46 | 2019 |
| Content-aware neural hashing for cold-start recommendation C Hansen, C Hansen, JG Simonsen, S Alstrup, C Lioma Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 44 | 2020 |
