Search results
Results: 368
Number of items: 368
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Dalbah, Y., Worring, M., & Hsu, Y.-C. (2026). Veli: Unsupervised Method and Unified Benchmark for Low-Cost Air Quality Sensor Correction. In S. Koenig, C. Jenkins, & M. Taylor (Eds.), Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence: January 20-January 27, 2026, Singapore (Vol. 25, pp. 20684-20692). AAAI Press. https://doi.org/10.1609/aaai.v40i25.39206 -
Efthymiou, A., Rudinac, S., Kackovic, M., Wijnberg, N., & Worring, M. (2026). VL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings. In WWW '26: Proceedings of the ACM Web Conference 2026 : April 13-17, 2026, Dubai, United Arab Emirates (pp. 7552-7563). Association for Computing Machinery. https://doi.org/10.1145/3774904.3792677 -
Li, M., Zhang, P., Xing, W., Zheng, Y., Zaporojets, K., Chen, J., Zhang, R., Zhang, Y., Gong, S., Hu, J., Ma, X., Liu, Z., Groth, P., & Worring, M. (2026). A survey of large language models for data challenges in graphs. Expert Systems With Applications, 298(A), Article 129643. https://doi.org/10.1016/j.eswa.2025.129643 -
Efthymiou, A., Kackovic, M., Rudinac, S., Worring, M., & Wijnberg, N. (2026). Being Ranked in a Material World: The visual originality of an artwork and its effects on the artist’s canonization. Organization Studies, 47(1), 93-125. https://doi.org/10.1177/01708406251397720, https://doi.org/10.1177/01708406251397720 -
McCarthy, C., Quirijnen, L., van Zandwijk, J. P., Geradts, Z., & Worring, M. (2025). Hi-OSCAR: Hierarchical Open-set Classifier for Human Activity Recognition. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 9(4), Article 199. https://doi.org/10.1145/3770681 -
Vasilcoiu, A., Najdenkoska, I., Geradts, Z., & Worring, M. (2025). LATTE: Latent Trajectory Embedding for Diffusion-Generated Image Detection. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2507.03054 -
Kombrink, M. H., Geradts, Z. J. M. H., & Worring, M. (2025). Image Steganography Approaches and Their Detection Strategies: A Survey. ACM Computing Surveys, 57(2), Article 33. https://doi.org/10.1145/3694965
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