ジャーナル論文 / Journal
  1. Wang, J., Xuan, W., Qi, H., Chen, Z., Chen, H., Zheng, Z., Xia, J., Zhong, Y., and Yokoya, N., "CityVLM: Towards sustainable urban development via multi-view coordinated vision–language model", ISPRS J. Photogramm. Remote Sens. 232, 62–74, (2026).
  2. WEI, Y., Xiao, A., Ren, Y., Zhu, Y., Chen, H., Xia , J., and Yokoya, N., "SARLANG-1M: A Benchmark for Vision–Language Modeling in SAR Image Understanding", IEEE Trans. Geosci. Remote Sensing, (2026).
  3. Ebel, P., Baz, M. E., Wang, J., Xuan, W., Qi, H., Zheng, Z., Yokoya, N., Park, J., Park, J., Elskens, A., Charles, E., Modica, I., Foltz, Z., Bally, P., Bossung, C., Chini, M., Longépé, N., and Meoni, G., "Artificial Intelligence for Earthquake Response: Outcomes and insights from a global spaceborne rapid mapping challenge", IEEE Geosci. Remote Sens. Mag., (2026).
  4. Xiao, A., Xuan, W., Wang, J., Huang, J., Tao, D., Lu, S., and Yokoya, N., "Foundation Models for Remote Sensing and Earth Observation: A survey", IEEE Geosci. Remote Sens. Mag. PP(99), 2–29, (2025).
  5. Ibañez, D., Fernandez-Beltran, R., Pla, F., Yokoya, N., and Xia, J., "Multi-modal consistent loss diffusion model for Sentinel-3 single image super resolution", Neural Computing and Applications 37(10), 7121–7143, (2025).
  6. Chen, H., Song, J., Dietrich, O., Broni-Bediako, C., Xuan, W., Wang, J., Shao, X., Wei, Y., Xia, J., Lan, C., Schindler, K., and Yokoya, N., "Bright: a globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response", Earth Syst. Sci. Data 17(11), 6217–6253, (2025).
  7. Yokoya, N., Xia, J., and Broni-Bediako, C., "Submeter-level land cover mapping of Japan", Int. J. Appl. Earth Obs. Geoinf. 127, 103660, (2024).
  8. Wang, Z., Zhang, F., Wu, C., and Xia, J., "Rapid mapping of volcanic eruption building damage: A model based on prior knowledge and few-shot fine-tuning", Int. J. Appl. Earth Obs. Geoinf. 126, 103622, (2024).
  9. Nakamura, S., and Sugiyama, M., "A fast algorithm for the real-valued combinatorial pure exploration of multi-armed bandit", Neural Comput. 37(2), 294–310, (2024).
  10. He, W., Wu, Z., Yokoya, N., and Yuan, X., "An interpretable and flexible fusion prior to boost hyperspectral imaging reconstruction", Information Fusion 111, 102528, (2024).
  11. Gan, W., Xu, H., Huang, Y., Chen, S., and Yokoya, N., "V4D: Voxel for 4D Novel View Synthesis", IEEE Trans. Visual. Comput. Graphics 30(2), 1579–1591, (2024).
  12. Gan, W., Mo, N., Xu, H., and Yokoya, N., "A Comprehensive Framework for 3D Occupancy Estimation in Autonomous Driving", IEEE Trans. Intell. Veh., (2024).
  13. Ding, X., Kang, J., Bai, Y., Zhang, A., Liu, J., and Yokoya, N., "Towards Robustness and Efficiency of Coherence-Guided Complex Convolutional Sparse Coding for Interferometric Phase Restoration", IEEE Trans. Comput. Imaging 10, 690–699, (2024).
  14. Cira, C., Manso-Callejo, M., Yokoya, N., Sălăgean, T., and Badea, A., "Impact of Tile Size and Tile Overlap on the Prediction Performance of Convolutional Neural Networks Trained for Road Classification", Remote Sensing 16(15), 2818, (2024).
  15. Chen, H., Song, J., Han, C., Xia, J., and Yokoya, N., "ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model", IEEE Trans. Geosci. Remote Sensing 62, 1–20, (2024).
  16. Chen, H., Lan, C., Song, J., Broni-Bediako, C., Xia, J., and Yokoya, N., "ObjFormer: Learning Land-Cover Changes From Paired OSM Data and Optical High-Resolution Imagery via Object-Guided Transformer", IEEE Trans. Geosci. Remote Sensing 62, 1–22, (2024).
  17. Broni-Bediako, C., Xia, J., Song, J., Chen, H., Siam, M., and Yokoya, N., "Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and Benchmark", IEEE Geosci. Remote. S. 21, 8003905, (2024).
  18. Xu, T., Huang, T., Deng, L., Dou, H., and Yokoya, N., "TR-STF: a fast and accurate tensor ring decomposition algorithm via defined scaled tri-factorization", Comput. Appl. Math. 42(5), 234, (2023).
  19. Shi, L., Zhang, F., Xia, J., and Xie, J., "Scene-level buildings damage recognition based on Cross Conv-Transformer", Int. J. Digital Earth 16(2), 3987–4007, (2023).
  20. Iizuka, R., Xia, J., and Yokoya, N., "Frequency-Based Optimal Style Mix for Domain Generalization in Semantic Segmentation of Remote Sensing Images", IEEE Trans. Geosci. Remote Sensing 62, 1–14, (2023).
  21. He, W., Uezato, T., and Yokoya, N., "Interpretable deep attention prior for image restoration and enhancement", IEEE Trans. Comput. Imaging 9, (2023).
  22. Chen, H., Yokoya, N., and Chini, M., "Fourier domain structural relationship analysis for unsupervised multimodal change detection", ISPRS J. Photogramm. Remote Sens. 198, 99–114, (2023).
  23. Chen, H., Song, J., Wu, C., Du, B., and Yokoya, N., "Exchange means change: An unsupervised single-temporal change detection framework based on intra- and inter-image patch exchange", ISPRS J. Photogramm. Remote Sens. 206, 87–105, (2023).
  24. Broni-Bediako, C., Xia, J., and Yokoya, N., "Real-Time Semantic Segmentation: A brief survey and comparative study in remote sensing", IEEE Geosci. Remote Sens. Mag. 11(4), 94–124, (2023).
国際会議 / Proceedings
  1. Yu, K., Zeng, Q., Xuan, W., Li, W., Wu, J., and Voigt, R., "The Pragmatic Mind of Machines: Tracing the Emergence of Pragmatic Competence in Large Language Models", The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026), (2026).
  2. Wu, F., Xuan, W., Qi, H., Lu, X., Tu, A., Li, L. E., and Choi, Y., "DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search", The Fourteenth International Conference on Learning Representations (ICLR 2026), (2026).
  3. Wu, F., Huang, X., Xuan, W., Zhang, Z., Xiao, Y., Wan, G., Li, X., Hu, B., Xia, P., Leskovec, J., and Choi, Y., "Multiplayer Nash Preference Optimization", The Fourteenth International Conference on Learning Representations (ICLR 2026), (2026).
  4. Tsujimoto, M., Wang, J., Xuan, W., and Yokoya, N., "Geo3DVQA: Evaluating Vision-Language Models for 3D Geospatial Reasoning from Aerial Imagery", The IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2026), (2026).
  5. Liu, Z., Liu, F., Xuan, W., and Yokoya, N., "LandCraft: Designing the Structured 3D Landscapes via Text Guidance", The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), (2026).
  6. Liu, J., Xuan, W., Jin, Z., and Diab, M., "Taming Object Hallucinations with Verified Atomic Confidence Estimation", The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026), (2026).
  7. Zhou, H., and Sugiyama, M., "Parallel simulation for sampling under isoperimetry and score-based diffusion models", Proceedings of the 42nd International Conference on Machine Learning, PMLR 267, 79192–79225, (2025).
  8. Zeng, Q., Xuan, W., Cui, L., and Voigt, R., "Thinking Out Loud: Do Reasoning Models Know When They're Right?", The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025 Main Conference), (2025).
  9. Xuan, W., Zeng, Q., Qi, H., Wang, J., and Yokoya, N., "Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models", 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), (2025).
  10. Xuan, W., Wang, J., Qi, H., Chen, Z., Zheng, Z., Zhong, Y., Xia, J., and Yokoya, N., "DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understanding", The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025), (2025).
  11. Wang, J., Xuan, W., Qi, H., Liu, Z., Liu, K., Wu, Y., Chen, H., Song, J., Xia, J., Zheng, Z., and Yokoya, N., "DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage Assessment and Response", The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025), (2025).
  12. Tang, Y., Zhang, Y., Ackermann, J., Zhang, Y., Nishimori, S., and Sugiyama, M., "Recursive reward aggregation", Reinforcement Learning Journal 2025 6, 923–975, (2025).
  13. Nishimori, S., Cai, X., Ackermann, J., and Sugiyama, M., "Offline reinforcement learning with domain-unlabeled data", Reinforcement Learning Journal 6, 1773–1793, (2025).
  14. Ning, C., Xuan, W., Gan, W., and Yokoya, N., "LR2Depth: Large-Region Aggregation at Low Resolution for Efficient Monocular Depth Estimation", 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 00, 618–625, (2025).
  15. Liu, Z., Cheng, Z., and Yokoya, N., "Neural Hierarchical Decomposition for Single Image Plant Modeling", 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 00, 733–742, (2025).
  16. Xiao, A., Xuan, W., Qi, H., Xing, Y., Ren, R., Zhang, X., Shao, L., and Lu, S., "CAT-SAM: Conditional Tuning for Few-Shot Adaptation of Segment Anything Model", The 18th European Conference on Computer Vision (ECCV 2024), (2024).
  17. Song, J., Chen, H., and Yokoya, N., "SyntheWorld: A large-scale synthetic dataset for land cover mapping and building change detection", 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), (2024).
  18. Song, J., Chen, H., Xuan, W., Xia, J., and Yokoya, N., "SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery", Advances in Neural Information Processing Systems 37 (NeurIPS 2024) 37, 117388–117425, (2024).
  19. Nakamura, S., and Sugiyama, M., "Thompson sampling for real-valued combinatorial pure exploration of multi-armed bandit", the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI2024), 14414–14421, (2024).
  20. Nakamura, S., and Sugiyama, M., "Fixed-budget real-valued combinatorial pure exploration of multi-armed bandit", Proceedings of 27th International Conference on Artificial Intelligence and Statistics (AISTATS2024) 238, 1225–1233, (2024).
  21. Liu, Z., Li, Y., Tu, F., Zhang, R., Cheng, Z., and Yokoya, N., "DeepTreeSketch: Neural Graph Prediction for Faithful 3D Tree Modeling from Sketches", CHI Conference on Human Factors in Computing Systems, (2024).
  22. Dong, X., and Yokoya, N., "Understanding dark scenes by contrasting multi-modal observations", 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), (2024).
  23. Adriano, B., Yokoya, N., Yamanoi, K., and Oishi, S., "Combining Deep Learning and Numerical Simulation to Predict Flood Inundation Depth", IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium 00, 1154–1157, (2023).
  24. Adriano, B., Yokoya, N., Yamanoi, K., and Oishi, S., "Predicting Flood Inundation Depth Based-on Machine Learning and Numerical Simulation", CEUR Workshop Proceedings 3207, 58–64, (2022).