Fine-tuning pre-trained transformer language models to distantly supervised relation extraction C Alt, M Hübner, L Hennig arXiv preprint arXiv:1906.08646, 2019 | 148 | 2019 |
TACRED revisited: A thorough evaluation of the TACRED relation extraction task C Alt, A Gabryszak, L Hennig arXiv preprint arXiv:2004.14855, 2020 | 145 | 2020 |
Topic-based Multi-Document Summarization with Probabilistic Latent Semantic Analysis. L Hennig RANLP, 144-149, 2009 | 132 | 2009 |
Improving relation extraction by pre-trained language representations C Alt, M Hübner, L Hennig arXiv preprint arXiv:1906.03088, 2019 | 113 | 2019 |
An ontology-based approach to text summarization L Hennig, W Umbrath, R Wetzker 2008 IEEE/WIC/ACM International Conference on Web Intelligence and …, 2008 | 76 | 2008 |
Layerwise relevance visualization in convolutional text graph classifiers R Schwarzenberg, M Hübner, D Harbecke, C Alt, L Hennig arXiv preprint arXiv:1909.10911, 2019 | 75 | 2019 |
Multi-objective optimization for the joint disambiguation of nouns and named entities D Weissenborn, L Hennig, F Xu, H Uszkoreit Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 48 | 2015 |
A hybrid PLSA approach for warmer cold start in folksonomy recommendation A Said, W Robert, W Umbrath, L Hennig Recommender Systems & the Social Web, 10-13, 2009 | 42 | 2009 |
Probing linguistic features of sentence-level representations in neural relation extraction C Alt, A Gabryszak, L Hennig arXiv preprint arXiv:2004.08134, 2020 | 35 | 2020 |
Abstractive text summarization based on language model conditioning and locality modeling D Aksenov, J Moreno-Schneider, P Bourgonje, R Schwarzenberg, ... arXiv preprint arXiv:2003.13027, 2020 | 30 | 2020 |
Sar-graphs: A language resource connecting linguistic knowledge with semantic relations from knowledge graphs S Krause, L Hennig, A Moro, D Weissenborn, F Xu, H Uszkoreit, R Navigli Journal of Web Semantics 37, 112-131, 2016 | 29 | 2016 |
Twitter geolocation prediction using neural networks P Thomas, L Hennig Language Technologies for the Challenges of the Digital Age: 27th …, 2018 | 24 | 2018 |
A german corpus for fine-grained named entity recognition and relation extraction of traffic and industry events M Schiersch, V Mironova, M Schmitt, P Thomas, A Gabryszak, L Hennig arXiv preprint arXiv:2004.03283, 2020 | 22 | 2020 |
Automatic layouting of personalized newspaper pages T Strecker, L Hennig Operations Research Proceedings 2008: Selected Papers of the Annual …, 2009 | 22 | 2009 |
Why only micro-f1? class weighting of measures for relation classification D Harbecke, Y Chen, L Hennig, C Alt arXiv preprint arXiv:2205.09460, 2022 | 18 | 2022 |
Bootstrapping named entity recognition in e-commerce with positive unlabeled learning H Zhang, L Hennig, C Alt, C Hu, Y Meng, C Wang arXiv preprint arXiv:2005.11075, 2020 | 16 | 2020 |
MOLI: Smart conversation agent for mobile customer service G Zhao, J Zhao, Y Li, C Alt, R Schwarzenberg, L Hennig, S Schaffer, ... Information 10 (2), 63, 2019 | 16 | 2019 |
Multilingual relation classification via efficient and effective prompting Y Chen, D Harbecke, L Hennig arXiv preprint arXiv:2210.13838, 2022 | 14 | 2022 |
DAI Approaches to the TAC-KBP 2011 Entity Linking Task. D Ploch, L Hennig, EW De Luca, S Albayrak, TU DAI-Labor TAC, 2011 | 14 | 2011 |
Learning comment controversy prediction in web discussions using incidentally supervised multi-task CNNs N Rethmeier, M Hübner, L Hennig Proceedings of the 9th Workshop on Computational Approaches to Subjectivity …, 2018 | 13 | 2018 |