Publications

Petsinis, P., Skitsas, K., Ranu, S., Mottin, D. & Karras, P. (2025). Alpine: Partial Unlabeled Graph Alignment. In KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2315-2325). Association for Computing Machinery. https://doi.org/10.1145/3711896.3736839

Ágústsson, S. Ý., Haque, M. A., Truong, T. T., Bianchi, M., Klyuchnikov, N., Mottin, D., Karras, P. & Hofmann, P. (2025). An autoencoder for compressing angle-resolved photoemission spectroscopy data. Machine Learning: Science and Technology, 6(1), Article 015019. https://doi.org/10.1088/2632-2153/ada8f2

Zhong, Z., Larsen, S. S.-Y., Guo, H., Tang, T., Zhou, K. & Mottin, D. (2025). Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language.

Zhong, Z., Larsen, S. S.-Y., Guo, H., Tang, T., Zhou, K. & Mottin, D. (2025). Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language. In L. Chiruzzo, A. Ritter & L. Wang (Eds.), 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Proceedings of the Conference Findings, NAACL 2025 (pp. 6192-6209). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.findings-naacl.345

Khani, P. & Assent, I. (2025). Causal Banzhaf Value for Aggregate Query Explanations. CEUR Workshop Proceedings, 3931, 54-58.

Quercia, A., Yildiz, E., Cao, Z., Krajsek, K., Morrison, A., Assent, I. & Scharr, H. (2025). Enhancing Monocular Depth Estimation with Multi-Source Auxiliary Tasks. In Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (pp. 6435-6445). IEEE. https://doi.org/10.1109/WACV61041.2025.00627

Krieger, L., Beer, A., Matthews, P., Thiesson, A. M. & Assent, I. (2025). FAIRDEN: FAIR DENSITY-BASED CLUSTERING. In 13th International Conference on Learning Representations, ICLR 2025 (pp. 19570-19589). International Conference on Learning Representations, ICLR.

Quercia, A., Nader, F., Morrison, A., Scharr, H. & Assent, I. (2025). Focal Sampling: SGD biased towards early important samples for efficient image classification with augmentation selection. Knowledge and Information Systems, 67(11), 11161-11191. https://doi.org/10.1007/s10115-025-02563-7

Sun, G., Karras, P. & Zhang, Q. (2025). Highly Efficient Direct Analytics on Semantic-Aware Time Series Data Compression. In M. Valenti, D. Reed & M. Torres (Eds.), ICC 2025 - IEEE International Conference on Communications (pp. 5945-5950). IEEE. https://doi.org/10.1109/ICC52391.2025.11162086

Truong, T. T., Airao, J., Fattahi, S., Azarhoushang, B., Karras, P. & Aghababaei, R. (2025). Image-based machine learning model for tool wear estimation in milling Inconel 718. Wear, 571, Article 205865. https://doi.org/10.1016/j.wear.2025.205865

Tran, H. V., Zhang, Z., Pham, T. D., Doan, N. P., Hoang, A.-T., Li, P., Vandierendonck, H., Assent, I. & Mai, T. S. (2025). InteDisUX: intepretation-guided discriminative user-centric explanation for time series. Proceedings of the AAAI Conference on Artificial Intelligence, 39(20), 20921-20928. https://doi.org/10.1609/aaai.v39i20.35387

Zhong, Z., Barkova, A. & Mottin, D. (2025). Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey. ACM Computing Surveys, 57(12), Article 302. https://doi.org/10.1145/3744237

Cao, Z., Zhao, X., Krieger, L., Scharr, H. & Assent, I. (2025). LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching. Poster session presented at The Thirty-ninth Annual Conference on Neural Information Processing Systems, San Diego, California, United States.

Pauli, A. B., Augenstein, I. & Assent, I. (2025). Measuring and Benchmarking Large Language Models’ Capabilities to Generate Persuasive Language. In L. Chiruzzo, A. Ritter & L. Wang (Eds.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 10056-10075). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.naacl-long.506

Pauli, A. B., Augenstein, I. & Assent, I. (2025). Mind the Style Gap: Meta-Evaluation of Style and Attribute Transfer Metrics. In C. Christodoulopoulos, T. Chakraborty, C. Rose & V. Peng (Eds.), EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2025: EMNLP 2025 (pp. 21550-21564). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.findings-emnlp.1175

Tran, H. V., Doan, N. P., Zhang, Z., Pham, T. D., Nguyen, P. H., Nguyen, X. H., Vandierendonck, H., Assent, I. & Mai, T. S. (2025). MIX: A Multi-view Time-Frequency Interactive Explanation Framework for Time Series Classification. Poster session presented at The Thirty-ninth Annual Conference on Neural Information Processing Systems, San Diego, California, United States. https://neurips.cc/virtual/2025/loc/san-diego/poster/117533

Skitsas, K., Mottin, D. & Karras, P. (2025). Pilos: Scalable Large-Subgraph Matching by Online Spectral Filtering. In Proceedings - 2025 IEEE 41st International Conference on Data Engineering, ICDE 2025 (pp. 1180-1193). IEEE. https://doi.org/10.1109/ICDE65448.2025.00093

Egger, M. K., Mottin, D. & Karras, P. (2025). Robust Knowledge Graph Cleaning. CEUR Workshop Proceedings, 3946. https://ceur-ws.org/Vol-3946/PhD-Workshop-1.pdf

Mortensen, K. O., Skitsas, K., Christensen, E. M., Talebi, M. S., Pavlogiannis, A., Mottin, D. & Karras, P. (2025). SwiftVI: Time-Efficient Planning and Learning with MDPs. In M. Zaharia, G. Joshi & Y. Lin (Eds.), Proceedings of Machine Learning and Systems (Vol. 7). MLSys. https://proceedings.mlsys.org/paper_files/paper/2025/file/0f8426558905746fc38da5e335700aec-Paper-Conference.pdf

Amer-Yahia, S., Bogojeska, J., Facchinetti, R., Franceschi, V., Gionis, A., Hose, K., Koutrika, G., Kouyos, R., Lissandrini, M., Maniu, S., Mirylenka, K., Mottin, D., Palpanas, T., Rigotti, M. & Velegrakis, Y. (2025). Towards Reliable Conversational Data Analytics. In roceedings of the 28th International Conference on Extending Database Technology (3 ed., pp. 962-969). openproceedings.org. https://doi.org/10.48786/edbt.2025.78

Draganov, A. A., Weber, P., Jørgensen, R. S. M., Beer, A., Plant, C. & Assent, I. (2025). Ultrametric Cluster Hierarchies: I Want ‘em All!. https://neurips.cc/media/PosterPDFs/NeurIPS%202025/119173.png?t=1762960797.979475

Moradan, A., Sorkhpar, M., Miyauchi, A., Mottin, D. & Assent, I. (2025). Untapping the Power of Indirect Relationships in Entity Summarization. In WSDM 2025 : Proceedings of the 18th ACM International Conference on Web Search and Data Mining (pp. 820-828). Association for Computing Machinery. https://doi.org/10.1145/3701551.3703566

Pfaehler, E., Krieger, L., Assent, I., Nebelung, S., Zwanenburg, A. & Truhn, D. (2025). Using ensemble radiomic models to identify uncertainty in lung nodule classifications. European Journal of Radiology Artificial Intelligence, 4, Article 100047. https://doi.org/10.1016/j.ejrai.2025.100047

Amico, T., Dada, S., Lazzari, A., Brezinova, M., Trovato, A., Vendruscolo, M., Fuxreiter, M. & Maritan, A. (2024). A scale-invariant log-normal droplet size distribution below the critical concentration for protein phase separation. eLife, 13, Article RP94214. https://doi.org/10.7554/eLife.94214.3

Ágústsson, S. Ý., Jones, A. J. H., Curcio, D., Ulstrup, S., Miwa, J., Mottin, D., Karras, P. & Hofmann, P. (2024). Autonomous micro-focus angle-resolved photoemission spectroscopy. Review of Scientific Instruments, 95(5), Article 055106. https://doi.org/10.1063/5.0204663

Hansen, S. M., Assent, I. & Schulz, H.-J. (2024). A Web Framework for Explainable and Malleable Visualisation. In K. Kucher, A. Diehl & C. Gillmann (Eds.), EuroVisPosters2024: Poster Proceedings of the 26th Eurographics Conference on Visualization The Eurographics Association. https://doi.org/10.2312/evp.20241080

Truong, T. T., Airao, J., Hojati, F., Ilvig, C. F., Azarhoushang, B., Karras, P. & Aghababaei, R. (2024). Data-driven prediction of tool wear using Bayesian regularized artificial neural networks. Measurement: Journal of the International Measurement Confederation, 238, Article 115303. https://doi.org/10.1016/j.measurement.2024.115303

Rodriguez, J. M., Tavassoli, N., Levy, E., Lederman, G., Sivov, D., Lissandrini, M. & Mottin, D. (2024). Does the Performance of Text-to-Image Retrieval Models Generalize Beyond Captions-as-a-Query? In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald & I. Ounis (Eds.), Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024, Proceedings, Part IV (pp. 161-176). Springer. https://doi.org/10.1007/978-3-031-56066-8_15

Beer, A., Palotás, O., Maldonado, A., Draganov, A. & Assent, I. (2024). DROPP: Structure-Aware PCA for Ordered Data: A General Method and its Applications in Climate Research and Molecular Dynamics. In 2024 IEEE 40th International Conference on Data Engineering (ICDE) (pp. 1143-1156). IEEE. https://doi.org/10.1109/ICDE60146.2024.00093

Zhong, Z. & Mottin, D. (2024). Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding. In A. Bifet, J. Davis, T. Krilavičius, M. Kull, E. Ntoutsi & I. Žliobaitė (Eds.), Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part VII (pp. 399-415). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-70368-3_24

Khani, P., Moeinaddini, E., Abnavi, N. D. & Shahraki, A. (2024). Explainable artificial intelligence for feature selection in network traffic classification: A comparative study. Transactions on Emerging Telecommunications Technologies, 35(4), Article e4970. https://doi.org/10.1002/ett.4970

Zhong, Z. & Mottin, D. (2024). Exploring Graph Structure Comprehension Ability of Multimodal Large Language Models: Case Studies.

Petsinis, P., Tsourakakis, C. E. & Karras, P. (2024). Finding Dense and Persistently Expansive Subgraphs. In WWW 2024 Companion - Companion Proceedings of the ACM Web Conference (pp. 553-556). Association for Computing Machinery. https://doi.org/10.1145/3589335.3651507

Bommakanti, A., Vonteri, H. R., Skitsas, K., Ranu, S., Mottin, D. & Karras, P. (2024). FUGAL: Feature-fortified Unrestricted Graph Alignment. Paper presented at The Thirty-eighth Annual Conference on Neural Information Processing Systems.

Cao, Z., Krieger, L., Scharr, H. & Assent, I. (2024). Galaxy Morphology Classification with Counterfactual Explanation. In Machine Learning and the Physical Sciences Workshop, NeurIPS 2024. https://ml4physicalsciences.github.io/2024/files/NeurIPS_ML4PS_2024_22.pdf

Zhong, Z., Zhou, K. & Mottin, D. (2024). Harnessing Large Language Models as Post-hoc Correctors. In L.-W. Ku, A. Martins & V. Srikumar (Eds.), Findings of the Association for Computational Linguistics: ACL 2024 (pp. 14559-14574). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.findings-acl.867

Huang, C., Mathiasen, A., Dean, J., Mottin, D. & Assent, I. (2024). HUNIPU: Efficient Hungarian Algorithm on IPUs. In Proceedings - 2024 IEEE 40th International Conference on Data Engineering Workshops, ICDEW 2024 (pp. 388-394). IEEE. https://doi.org/10.1109/ICDEW61823.2024.00062

Ma, W., Egger, M. K., Pavlogiannis, A., Li, Y. & Karras, P. (2024). Reachability-Aware Fair Influence Maximization. In W. Zhang, Z. Yang, X. Wang, A. Tung, Z. Zheng & H. Guo (Eds.), Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Proceedings: 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 – September 1, 2024, Proceedings, Part III (pp. 342-359). BMJ, Springer Nature. https://doi.org/10.1007/978-981-97-7238-4_22

Egger, M. K., Ma, W., Mottin, D., Karras, P., Bordino, I., Gullo, F. & Anagnostopoulos, A. (2024). ReliK: A Reliability Measure for Knowledge Graph Embeddings. In WWW '24 : Proceedings of the ACM Web Conference (pp. 2009-2019). Association for Computing Machinery. https://doi.org/10.1145/3589334.3645430

Petsinis, P., Zhang, K., Pavlogiannis, A., Zhou, J. & Karras, P. (2024). Robust Reward Placement under Uncertainty. In K. Larson (Ed.), Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 (pp. 6770-6778). International Joint Conferences on Artificial Intelligence Organization. https://doi.org/10.24963/ijcai.2024/748

Petsinis, P., Pavlogiannis, A., Tkadlec, J. & Karras, P. (2024). Seed Selection in the Heterogeneous Moran Process. In K. Larson (Ed.), Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 (pp. 2297-2305). International Joint Conferences on Artificial Intelligence Organization. https://doi.org/10.24963/ijcai.2024/254

Tommasel, A. & Assent, I. (2024). Semantic grounding of LLMs using knowledge graphs for query reformulation in medical information retrieval. In W. Ding, C.-T. Lu, F. Wang, L. Di, K. Wu, J. Huan, R. Nambiar, J. Li, F. Ilievski, R. Baeza-Yates & X. Hu (Eds.), 2024 IEEE International Conference on Big Data (BigData) (pp. 4048-4057). IEEE. https://doi.org/10.1109/BigData62323.2024.10826117, https://doi.org/10.1109/BigData62323.2024.10826117

Aminimehr, A., Khani, P., Molaei, A., Kazemeini, A. & Cambria, E. (2024). TbExplain: A Text-Based Explanation Method for Scene Classification Models with the Statistical Prediction Correction. In GUIDE-AI '24: Proceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI (pp. 54-60). Association for Computing Machinery. https://doi.org/10.1145/3665601.3669841

Draganov, A., Jørgensen, J., Scheel, K., Mottin, D., Assent, I., Berry, T. & Aslay, C. (2023). ActUp: Analyzing and Consolidating tSNE & UMAP. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 3651-3658). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/406

Lampropoulos, K., Zardbani, F., Mamoulis, N. & Karras, P. (2023). Adaptive Indexing in High-Dimensional Metric Spaces. Proceedings of the VLDB Endowment, 16(10), 2525-2537. https://doi.org/10.14778/3603581.3603592

Zardbani, F., Mamoulis, N., Idreos, S. & Karras, P. (2023). Adaptive Indexing of Objects with Spatial Extent. Proceedings of the VLDB Endowment, 16(9), 2248-2260. https://doi.org/10.14778/3598581.3598596

Pauli, A. B., Derczynski, L. & Assent, I. (2023). Anchoring Fine-tuning of Sentence Transformer with Semantic Label Information for Efficient Truly Few-shot Classification. In H. Bouamor, J. Pino & K. Bali (Eds.), Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (pp. 11254–11264). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.692

Chatzopoulos, S., Vergoulis, T., Skoutas, D., Dalamagas, T., Tryfonopoulos, C. & Karras, P. (2023). Atrapos: Real-time Evaluation of Metapath Query Workloads. In ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023 (pp. 2487-2498). Association for Computing Machinery. https://doi.org/10.1145/3543507.3583322

Skitsas, K., Orłowski, K., Hermanns, J., Mottin, D. & Karras, P. (2023). Comprehensive Evaluation of Algorithms for Unrestricted Graph Alignment. In Proceedings 26th International Conference on Extending Database Technology (EDBT 2023) (pp. 260-272). openproceedings.org. https://doi.org/10.48786/edbt.2023.21

Displaying results 1 to 50 out of 242

Revised 01.09.2025

Sofia Hedegaard Rasmussen