2022
Spliethöver, M., Keiff, M., & Wachsmuth, H. (2022). No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media. in Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022) Association for Computational Linguistics.
Stahl, M., Spliethöver, M., & Wachsmuth, H. (2022). To Prefer or to Choose? Generating Agency and Power Counterfactuals Jointly for Gender Bias Mitigation. in Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (S. 39-51). (NLPCSS 2022 - 5th Workshop on Natural Language Processing and Computational Social Science ,NLP+CSS, Held at the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022). Association for Computational Linguistics (ACL).
Tornede, A., Bengs, V., & Hüllermeier, E. (2022). Machine Learning for Online Algorithm Selection under Censored Feedback. in Proceedings of the 36th AAAI Conference on Artificial Intelligence (S. 10370-10380)
Wachsmuth, H., & Alshomary, M. (2022). "Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain. in Proceedings of the 29th International Conference on Computational Linguistics (S. 344 - 354). International Committee on Computational Linguistics.
2021
Ajjour, Y., Al-Khatib, K., Cimiano, P., El Baff, R., Ell, B., Stein, B., & Wachsmuth, H. (2021). Preface. CEUR Workshop Proceedings, 2921.
Ajjour, Y., Al-Khatib, K., Cimiano, P., Baff, R. E., Ell, B., Stein, B., & Wachsmuth, H. (Hrsg.) (2021). Same Side Stance Classification Shared Task 2019. (CEUR Workshop Proceedings).
Al-Khatib, K., Trautner, L., Wachsmuth, H., Hou, Y., & Stein, B. (2021). Employing argumentation knowledge graphs for neural argument generation. in ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference (S. 4744-4754). Association for Computational Linguistics (ACL).
Alshomary, M., Chen, W. F., Gurcke, T., & Wachsmuth, H. (2021). Belief-based Generation of Argumentative Claims. in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (S. 224-233). Association for Computational Linguistics (ACL).
doi.org/10.48550/arXiv.2101.09765
,Alshomary, M., Syed, S., Dhar, A., Potthast, M., & Wachsmuth, H. (2021). Counter-Argument Generation by Attacking Weak Premises: Counter-Argument Generation by Attacking Weak Premises. in C. Zong, F. Xia, W. Li, & R. Navigli (Hrsg.), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (S. 1816-1827). Association for Computational Linguistics (ACL).
Alshomary, M., Gurke, T., Syed, S., Heinisch, P., Spliethöver, M., Cimiano, P., Potthast, M., & Wachsmuth, H. (2021). Key Point Analysis via Contrastive Learning and Extractive Argument Summarization. in Proceedings of The 8th Workshop on Argument Mining, (S. 184-189). Association for Computational Linguistics (ACL).
Alshomary, M., & Wachsmuth, H. (2021). Toward audience-aware argument generation. Patterns, 2(6), [100253].
Barrow, J., Jain, R., Lipka, N., Dernoncourt, F., Morariu, V. I., Manjunatha, V., Oard, D. W., Resnik, P., & Wachsmuth, H. (2021). Syntopical graphs for computational argumentation tasks. in Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (S. 1583-1595). Association for Computational Linguistics (ACL).
Benjamins, C., Eimer, T., Schubert, F., Biedenkapp, A., Rosenhahn, B., Hutter, F., & Lindauer, M. (2021). CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning. in Workshop on Ecological Theory of Reinforcement Learning, NeurIPS 2021
Biedenkapp, A., Rajan, R., Hutter, F., & Lindauer, M. (2021). TempoRL: Learning When to Act. in Proceedings of the international conference on machine learning (ICML)
Bondarenko, A., Gienapp, L., Fröbe, M., Beloucif, M., Ajjour, Y., Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., Potthast, M., & Hagen, M. (2021). Overview of Touché 2021: Argument Retrieval: Extended Abstract. in D. Hiemstra, M-F. Moens, J. Mothe, R. Perego, M. Potthast, & F. Sebastiani (Hrsg.), Advances in Information Retrieval: 43rd European Conference on IR Research, Proceedings (S. 574-582). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12657 LNCS). Springer Science and Business Media Deutschland GmbH.
Bondarenko, A., Gienapp, L., Fröbe, M., Beloucif, M., Ajjour, Y., Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., Potthast, M., & Hagen, M. (2021). Overview of Touché 2021: Argument retrieval. CEUR Workshop Proceedings, 2936, 2258-2284.
Bondarenko, A., Gienapp, L., Fröbe, M., Beloucif, M., Ajjour, Y., Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., Potthast, M., & Hagen, M. (2021). Overview of Touché 2021: Argument Retrieval. in K. S. Candan, B. Ionescu, L. Goeuriot, H. Müller, A. Joly, M. Maistro, F. Piroi, G. Faggioli, & N. Ferro (Hrsg.), Experimental IR Meets Multilinguality, Multimodality, and Interaction. 12th International Conference of the CLEF Association (CLEF 2021) (Band 12880, S. 450-467). (Lecture Notes in Computer Science). Springer.
Chen, W. F., Al-Khati, K., Stein, B., & Wachsmuth, H. (2021). Controlled Neural Sentence-Level Reframing of News Articles. in M-F. Moens, X. Huang, L. Specia, & S. W-T. Yih (Hrsg.), Findings of the Association for Computational Linguistics: EMNLP 2021 (S. 2683-2693). Association for Computational Linguistics (ACL).
Eggensperger, K., Müller, P., Mallik, N., Feurer, M., Sass, R., Awad, N., Lindauer, M., & Hutter, F. (2021). HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. in Proceedings of the international conference on Neural Information Processing Systems (NeurIPS) (Datasets and Benchmarks Track)
Eimer, T., Biedenkapp, A., Reimer, M., Adriaensen, S., Hutter, F., & Lindauer, M. T. (2021). DACBench: A Benchmark Library for Dynamic Algorithm Configuration. in Z-H. Zhou (Hrsg.), Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) (S. 1668-1674). (IJCAI International Joint Conference on Artificial Intelligence).
Eimer, T., Benjamins, C., & Lindauer, M. T. (2021). Hyperparameters in Contextual RL are Highly Situational. in International Workshop on Ecological Theory of RL (at NeurIPS)
Eimer, T., Biedenkapp, A., Hutter, F., & Lindauer, M. (2021). Self-Paced Context Evaluation for Contextual Reinforcement Learning. in Proceedings of the international conference on machine learning (ICML)
Guerrero-Viu, J., Hauns, S., Izquierdo, S., Miotto, G., Schrodi, S., Biedenkapp, A., Elsken, T., Deng, D., Lindauer, M., & Hutter, F. (2021). Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization. in ICML 2021 Workshop AutoML
Gurcke, T., Alshomary, M., & Wachsmuth, H. (2021). Assessing the Sufficiency of Arguments through Conclusion Generation. in 8th Workshop on Argument Mining, ArgMining 2021 - Proceedings (S. 67-77). Association for Computational Linguistics (ACL).
Hanselle, J., Tornede, A., Wever, M., & Hüllermeier, E. (2021). Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. in K. Karlapalem, H. Cheng, N. Ramakrishnan, R. K. Agrawal, P. K. Reddy, J. Srivastava, & T. Chakraborty (Hrsg.), Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Proceedings: PAKDD 2021: Advances in Knowledge Discovery and Data Mining (Band 12712, S. 152-163). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12712 LNAI).
Hüllermeier, E., Mohr, F., Tornede, A., & Wever, M. (2021). Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. in ECML/PKDD workshop on Automating Data Science (ADS 2021)
Kadra, A., Lindauer, M., Hutter, F., & Grabocka, J. (2021). Well-tuned Simple Nets Excel on Tabular Datasets. in Proceedings of the international conference on Advances in Neural Information Processing Systems (NeurIPS 2021)
Kiesel, J., Spina, D., Wachsmuth, H., & Stein, B. (2021). The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases. in Proceedings of the 3rd Conference on Conversational User Interfaces, CUI 2021 [20] Association for Computing Machinery (ACM).
Kiesel, D., Riehmann, P., Wachsmuth, H., Stein, B., & Froehlich, B. (2021). Visual Analysis of Argumentation in Essays. IEEE Transactions on Visualization and Computer Graphics, 27(2), 1139-1148. [9222553].
Liu, Z., Pavao, A., Xu, Z., Escalera, S., Ferreira, F., Guyon, I., Hong, S., Hutter, F., Ji, R., Junior, J. C. S. J., Li, G., Lindauer, M., Luo, Z., Madadi, M., Nierhoff, T., Niu, K., Pan, C., Stoll, D., Treguer, S., ... Zhang, Y. (2021). Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(9), 3108-3125. [9415128].
doi.org/10.48550/arXiv.2201.03801
,Mohr, F., Wever, M., Tornede, A., & Hüllermeier, E. (2021). Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(9), 3055-3066. [9347828].
Moosbauer, J., Herbinger, J., Casalicchio, G., Lindauer, M., & Bischl, B. (2021). Explaining Hyperparameter Optimization via Partial Dependence Plots. in Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)
Nouri, Z., Prakash, N., Gadiraju, U., & Wachsmuth, H. (2021). iClarify: A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing. in Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021 AAAI Press/International Joint Conferences on Artificial Intelligence.
www.humancomputation.com/2021/assets/wips_demos/HCOMP_2021_paper_111.pdf
Nouri, Z., Gadiraju, U., Engels, G., & Wachsmuth, H. (2021). What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing. in HT 2021 - Proceedings of the 32nd ACM Conference on Hypertext and Social Media (S. 165-175). Association for Computing Machinery, Inc.
Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Hab-Umbach, R., Horwath, I., Hullermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A. C., Schulte, C., Wachsmuth, H., Wagner, P., & Wrede, B. (2021). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions on Cognitive and Developmental Systems, 13(3), 717-728. [9292993].
Schubert, F., Eimer, T., Rosenhahn, B., & Lindauer, M. (2021). Automatic Risk Adaptation in Distributional Reinforcement Learning.
Skitalinskaya, G., Klaff, J., & Wachsmuth, H. (2021). Learning from revisions: Quality assessment of claims in argumentation at scale. in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (S. 1718-1729). Association for Computational Linguistics (ACL).
doi.org/10.48550/arXiv.2101.10250
,Souza, A., Nardi, L., Oliveira, L. B., Olukotun, K., Lindauer, M., & Hutter, F. (2021). Bayesian Optimization with a Prior for the Optimum. in N. Oliver, F. Pérez-Cruz, S. Kramer, J. Read, & J. A. Lozano (Hrsg.), Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Proceedings (Band 3, S. 265-296). (Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science); Band 12977). Springer Nature Switzerland AG.
Souza, A., Nardi, L., Oliveira, L. B., Olukotun, K., Lindauer, M., & Hutter, F. (2021). Prior-guided Bayesian Optimization. in Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021
Speck, D., Biedenkapp, A., Hutter, F., Mattmüller, R., & Lindauer, M. (2021). Learning Heuristic Selection with Dynamic Algorithm Configuration. in Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS)
Spliethöver, M., & Wachsmuth, H. (2021). Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models. in Z-H. Zhou (Hrsg.), Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 (S. 552-559). (IJCAI International Joint Conference on Artificial Intelligence). AAAI Press/International Joint Conferences on Artificial Intelligence.
Stein, B., Ajjour, Y., El Baff, R., Al-Khatib, K., Cimiano, P., & Wachsmuth, H. (2021). Same side stance classification. CEUR Workshop Proceedings, 2921, 1-7.
