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Results: 116
Number of items: 116
  • Open Access
    Ayoughi, M., Mettes, P., & Groth, P. (2025). Minimizing Hyperbolic Embedding Distortion with LLM-Guided Hierarchy Restructuring. In K-CAP '25: Proceedings of the 13th Knowledge Capture Conference 2025 : Dayton, Ohio, USA (pp. 123-130). Association for Computing Machinery. https://doi.org/10.1145/3731443.3771357
  • Open Access
    Grafberger, S., Groth, P., & Schelter, S. (2024). Towards Interactively Improving ML Data Preparation Code via “Shadow Pipelines”. In Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning (DEEM): in conjunction with the 2024 ACM SIGMOD/PODS Conference, Santiago, Chile (pp. 7–11). The Association for Computing Machinery. https://doi.org/10.1145/3650203.3663327
  • Open Access
    Zhang, P., Cao, C., Zaporojets, K., & Groth, P. (2024). CYCLE: Cross-Year Contrastive Learning in Entity-Linking. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 3197-3206). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679702
  • Open Access
    Groth, P., Blomqvist, E., & Sequeda, J. F. (2024). Editorial for the Special Issue on Knowledge Engineering. Journal of Web Semantics, 83, Article 100840. https://doi.org/10.1016/j.websem.2024.100840
  • Open Access
    Karabulut, E., Groth, P., & Degeler, V. (2024). 3K: Knowledge-Enriched Digital Twin Framework. In Proceedings of the 14th International Conference on the Internet of Things 2024: IoT2024 : Oulu, Finland, 19.-22. Nov 2024 (pp. 188-193). Association for Computing Machinery. https://doi.org/10.1145/3703790.3703834
  • Open Access
    Soiland-Reyes, S., Goble, C., & Groth, P. (2024). Evaluating FAIR Digital Object and Linked Data as distributed object systems. PeerJ Computer Science, 10, Article e1781. https://doi.org/10.7717/PEERJ-CS.1781
  • Open Access
    Nevin, J. G. (2024). The ramifications of data handling for computational models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Hulsebos, M. (2024). Table Representation Learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Hendriksen, M. Y. (2024). Multimodal machine learning for information retrieval: A vision and language perspective. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Allen, B. P., Polat, F., & Groth, P. (2024). SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection. In A. K. Ojha, A. S. Doğruöz, H. T. Madabushi, G. Da San Martino, S. Rosenthal, & A. Rosá (Eds.), The 18th International Workshop on Semantic Evaluation (SemEval-2024) : proceedings of the workshop: SemEval 2024 : June 20-21, 2024 (pp. 839-844). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.semeval-1.120
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