Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking S Hofstätter, M Zlabinger, A Hanbury European Conference on Artificial Intelligence (ECAI), 2020 | 88 | 2020 |
Developing a fully automated evidence synthesis tool for identifying, assessing and collating the evidence J Brassey, C Price, J Edwards, M Zlabinger, A Bampoulidis, A Hanbury BMJ Evidence-Based Medicine 26 (1), 24-27, 2019 | 21 | 2019 |
Mitigating the position bias of transformer models in passage re-ranking S Hofstätter, A Lipani, S Althammer, M Zlabinger, A Hanbury Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021 | 20 | 2021 |
TU Wien@ TREC Deep Learning'19--Simple Contextualization for Re-ranking S Hofstätter, M Zlabinger, A Hanbury arXiv preprint arXiv:1912.01385, 2019 | 18 | 2019 |
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering S Hofstätter, M Zlabinger, M Sertkan, M Schröder, A Hanbury Conference on Information & Knowledge Management (CIKM), 3031-3038, 2020 | 11 | 2020 |
Medical Entity Corpus with PICO Elements and Sentiment Analysis M Zlabinger, L Andersson, A Hanbury, M Andersson, V Quasnik, ... International Conference on Language Resources and Evaluation (LREC), 2018 | 10 | 2018 |
Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports M Zlabinger, M Sabou, S Hofstätter, A Hanbury Conference on Empirical Methods in Natural Language Processing (EMNLP …, 2020 | 8 | 2020 |
Learning to Re-Rank with Contextualized Stopwords S Hofstätter, A Lipani, M Zlabinger, A Hanbury Conference on Information & Knowledge Management (CIKM), 2057-2060, 2020 | 6 | 2020 |
Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-ranking Results S Hofstätter, M Zlabinger, A Hanbury European Conference on Information Retrieval (ECIR), 459-464, 2020 | 6 | 2020 |
Extracting the Population, Intervention, Comparison and Sentiment from Randomized Controlled Trials. M Zlabinger, L Andersson, J Brassey, A Hanbury Medical Informatics Europe Conference (MIE), 146-150, 2018 | 6 | 2018 |
DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts M Zlabinger, M Sabou, S Hofstätter, M Sertkan, A Hanbury SIGIR Conference on Research and Development in Information Retrieval, 2109-2112, 2020 | 5 | 2020 |
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations M Zlabinger, S Hofstätter, N Rekabsaz, A Hanbury European Conference on Information Retrieval (ECIR), 433-440, 2020 | 4 | 2020 |
Finding Duplicate Images in Biology Papers M Zlabinger, A Hanbury Proceedings of the Symposium on Applied Computing (SAC), 957-959, 2017 | 4 | 2017 |
Efficient and Effective Text-Annotation through Active Learning M Zlabinger SIGIR Conference on Research and Development in Information Retrieval, 1456-1456, 2019 | 3 | 2019 |
Verifying Extended Entity Relationship Diagrams with Open Tasks M Sabou, K Käsznar, M Zlabinger, S Biffl, D Winkler Conference on Human Computation and Crowdsourcing (HCOMP) 8 (1), 132-140, 2020 | 2 | 2020 |
Efficient answer-annotation for frequent questions M Zlabinger, N Rekabsaz, S Zlabinger, A Hanbury Conference of the Cross-Language Evaluation Forum (CLEF), 126-137, 2019 | 2 | 2019 |
Improving the Annotation Efficiency and Effectiveness in the Text Domain M Zlabinger European Conference on Information Retrieval (ECIR), 343-347, 2019 | 2 | 2019 |
SCI-3000: A Dataset for Figure, Table and Caption Extraction from Scientific PDFs F Darmanović, A Hanbury, M Zlabinger International Conference on Document Analysis and Recognition, 234-251, 2023 | 1 | 2023 |
Efficient and effective manual corpus annotation to create resources for evaluation and machine learning M Zlabinger Technische Universität Wien, 2021 | | 2021 |