| Does label smoothing mitigate label noise? M Lukasik, S Bhojanapalli, A Menon, S Kumar International Conference on Machine Learning, 6448-6458, 2020 | 377 | 2020 |
| Scaling graph neural networks with approximate pagerank A Bojchevski, J Gasteiger, B Perozzi, A Kapoor, M Blais, B Rózemberczki, ... Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 295 | 2020 |
| Hawkes processes for continuous time sequence classification: an application to rumour stance classification in twitter M Lukasik, PK Srijith, D Vu, K Bontcheva, A Zubiaga, T Cohn Proceedings of 54th Annual Meeting of the Association for Computational …, 2016 | 183 | 2016 |
| Discourse-aware rumour stance classification in social media using sequential classifiers A Zubiaga, E Kochkina, M Liakata, R Procter, M Lukasik, K Bontcheva, ... Information Processing & Management 54 (2), 273-290, 2018 | 163 | 2018 |
| Stance classification in rumours as a sequential task exploiting the tree structure of social media conversations A Zubiaga, E Kochkina, M Liakata, R Procter, M Lukasik arXiv preprint arXiv:1609.09028, 2016 | 139 | 2016 |
| Classifying Tweet Level Judgements of Rumours in Social Media M Lukasik, T Cohn, K Bontcheva The 2015 Conference on Empirical Methods on Natural Language Processing., 2015 | 99 | 2015 |
| Large language models with controllable working memory D Li, AS Rawat, M Zaheer, X Wang, M Lukasik, A Veit, F Yu, S Kumar arXiv preprint arXiv:2211.05110, 2022 | 87 | 2022 |
| Text segmentation by cross segment attention M Lukasik, B Dadachev, G Simoes, K Papineni arXiv preprint arXiv:2004.14535, 2020 | 82 | 2020 |
| Gaussian processes for rumour stance classification in social media M Lukasik, K Bontcheva, T Cohn, A Zubiaga, M Liakata, R Procter ACM Transactions on Information Systems (TOIS) 37 (2), 1-24, 2019 | 45 | 2019 |
| Point process modelling of rumour dynamics in social media M Lukasik, T Cohn, K Bontcheva Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 45 | 2015 |
| Pheme: computing veracity: the fourth challenge of big social data L Derczynski, K Bontcheva, M Lukasik, T Declerck, A Scharl, G Georgiev, ... | 44 | 2014 |
| Teacher's pet: understanding and mitigating biases in distillation M Lukasik, S Bhojanapalli, AK Menon, S Kumar arXiv preprint arXiv:2106.10494, 2021 | 27 | 2021 |
| Is pagerank all you need for scalable graph neural networks A Bojchevski, J Klicpera, B Perozzi, M Blais, A Kapoor, M Lukasik, ... ACM KDD, MLG Workshop, 2019 | 26 | 2019 |
| Longitudinal modeling of social media with Hawkes process based on users and networks PK Srijith, M Lukasik, K Bontcheva, T Cohn Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017 | 24 | 2017 |
| Using Gaussian processes for rumour stance classification in social media M Lukasik, K Bontcheva, T Cohn, A Zubiaga, M Liakata, R Procter arXiv preprint arXiv:1609.01962, 2016 | 22 | 2016 |
| Modeling Tweet Arrival Times using Log-Gaussian Cox Processes M Lukasik, PK Srijith, T Cohn, K Bontcheva The 2015 Conference on Empirical Methods on Natural Language Processing., 2015 | 22 | 2015 |
| Semantic label smoothing for sequence to sequence problems M Lukasik, H Jain, AK Menon, S Kim, S Bhojanapalli, F Yu, S Kumar arXiv preprint arXiv:2010.07447, 2020 | 21 | 2020 |
| Leveraging redundancy in attention with reuse transformers S Bhojanapalli, A Chakrabarti, A Veit, M Lukasik, H Jain, F Liu, YW Chang, ... arXiv preprint arXiv:2110.06821, 2021 | 20 | 2021 |
| Computational approach to dendritic spine taxonomy and shape transition analysis G Bokota, M Magnowska, T Kuśmierczyk, M Łukasik, M Roszkowska, ... Frontiers in Computational Neuroscience 10, 140, 2016 | 20 | 2016 |
| Evaluation of features for author name disambiguation using linear support vector machines PJ Dendek, L Bolikowski, M Lukasik 2012 10th IAPR International Workshop on Document Analysis Systems, 440-444, 2012 | 18 | 2012 |
Sanjiv KumarGoogle Fellow, VP, Google ResearchEmail verificata su google.com
