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Results: 5
Number of items: 5
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Liu, J., Shen, J., Zhou, P., Sonke, J.-J., & Gavves, E. (2025). Probabilistic Prototype Calibration of Vision-Language Models for Generalized Few-shot Semantic Segmentation. In 2025 IEEE/CVF International Conference on Computer Vision: ICCV 2025 : Honolulu, Hawaii, USA, 19-23 October 2025 : proceedings (pp. 21155-21165). IEEE Computer Society. https://doi.org/10.48550/arXiv.2506.22979, https://doi.org/10.1109/ICCV51701.2025.01965 -
Liu, J., Zhou, P., Xiao, Z., Shen, J., Yin, W., Sonke, J.-J., & Gavves, E. (2025). Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes. Proceedings of Machine Learning Research, 267, 40194-40213. https://openreview.net/forum?id=6qNbVtKGY2 -
Chen, J., Yang, Z., Shen, Y., Liu, J., Belloum, A., Grosso, P., & Papagianni, C. (2025). SurveyGen-I: Consistent Scientific Survey Generation with Evolving Plans and Memory-Guided Writing. In K. Inui, S. Sakti, H. Wang, D. F. Wong, P. Bhattacharyya, B. Banerjee, A. Ekbal, T. Chakraborty, & D. P. Singh (Eds.), The 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics: proceedings of the conference : IJCNLP-AACL 2025 : December 20-24, 2025 (Vol. 1, pp. 3687–3714). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.ijcnlp-long.193 -
Liu, J., Zhou, P., Du, Y., Tan, A.-H., Snoek, C. G. M., Sonke, J.-J., & Gavves, E. (2025). CaPo: Cooperative Plan Optimization for Efficient Embodied Multi-Agent Cooperation. In The Thirteenth International Conference on Learning Representations: ICLR 2025 https://openreview.net/forum?id=KRv9NubipP -
Liu, J., Yin, W., Wang, H., Chen, Y., Sonke, J.-J., & Gavves, E. (2024). Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation. In 2024 International Conference in 3D Vision: 3DV 2024 : 18-21 March 2024, Davos, Switzerland : proceedings (pp. 810-819). IEEE Computer Society. https://doi.org/10.1109/3DV62453.2024.00045
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