| Text processing like humans do: Visually attacking and shielding NLP systems S Eger, GG Şahin, A Rücklé, JU Lee, C Schulz, M Mesgar, K Swarnkar, ... Proceedings of the 2019 Conference of the North {A}merican Chapter of the …, 2019 | 127 | 2019 |
| A neural local coherence model for text quality assessment M Mesgar, M Strube Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 79 | 2018 |
| Generating coherent summaries of scientific articles using coherence patterns D Parveen, M Mesgar, M Strube Proceedings of the 2016 conference on empirical methods in natural language …, 2016 | 59 | 2016 |
| Graph-based coherence modeling for assessing readability M Mesgar, M Strube Proceedings of the fourth joint conference on lexical and computational …, 2015 | 41 | 2015 |
| Lexical coherence graph modeling using word embeddings M Mesgar, M Strube Proceedings of the 2016 Conference of the North American Chapter of the …, 2016 | 33 | 2016 |
| Generating persona-consistent dialogue responses using deep reinforcement learning M Mesgar, E Simpson, Y Wang, I Gurevych Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 26* | 2021 |
| Dialogue coherence assessment without explicit dialogue act labels M Mesgar, S Bücker, I Gurevych Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 26* | 2020 |
| Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation Y Gao, C M. Meyer, M Mesgar, I Gurevych Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 24 | 2019 |
| Using a graph-based coherence model in document-level machine translation L Born, M Mesgar, M Strube Proceedings of the Third Workshop on Discourse in Machine Translation, 26-35, 2017 | 13 | 2017 |
| Normalized entity graph for computing local coherence M Mesgar, M Strube Proceedings of TextGraphs-9: the workshop on Graph-based Methods for Natural …, 2014 | 12 | 2014 |
| A neural graph-based local coherence model M Mesgar, LFR Ribeiro, I Gurevych Findings of the Association for Computational Linguistics: EMNLP 2021, 2316-2321, 2021 | 5 | 2021 |
| Feature-rich error detection in scientific writing using logistic regression M Remse, M Mesgar, M Strube Proceedings of the 11th Workshop on Innovative Use of NLP for Building …, 2016 | 4 | 2016 |
| When is acl's deadline? a scientific conversational agent M Mesgar, P Youssef, L Li, D Bierwirth, Y Li, CM Meyer, I Gurevych arXiv preprint arXiv:1911.10392, 2019 | 3 | 2019 |
| Python Code Generation by Asking Clarification Questions HSX Li, M Mesgar, AFT Martins, I Gurevych Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 2* | 2023 |
| Neural Network in Human Identification by DNA Sequences R Rafeh, M Mesgar 2009 Second International Conference on Computer and Electrical Engineering …, 2009 | 2 | 2009 |
| The Devil is in the Details: On Models and Training Regimes for Few-Shot Intent Classification M Mesgar, TT Tran, G Glavas, I Gurevych Proceedings of the 17th Conference of the European Chapter of the …, 2023 | 1 | 2023 |
| History Based Unsupervised Data Oriented Parsing M Mesgar, G Ghassem-Sani Proceedings of the International Conference Recent Advances in Natural …, 2013 | 1 | 2013 |
| A Dataset of Argumentative Dialogues on Scientific Papers F Ruggeri, M Mesgar, I Gurevych Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | | 2023 |
| A Natural Language Interface for an Energy System Model J Hulsmann, LJ Sieben, M Mcsgar, F Steinke 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 1-5, 2021 | | 2021 |
| Graph-based Patterns for Local Coherence Modeling M Mesgar | | 2020 |
Iryna GurevychFull Professor, TU Darmstadt; Adjunct Professor, MBZUAI, Abu DhabiVerified email at cs.tu-darmstadt.de
