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In the age of cloud computing, data privacy protection has become a major challenge, especially when sharing sensitive data across cloud environments.
J. Bosch, H. H. Olsson, and I. Crnkovic, “Engineering AI systems: A research agenda,”
2021
Earlier work this paper cites.
J. He, C. I. Kanatsoulis, and A. Ribeiro, “T-GAE: Transferable graph autoencoder for network alignment,”
2023
Earlier work this paper cites.
Y. Guo, “Optimization of privacy-aware cloud crowdsourcing resource combinations for product development,”
2023
Earlier work this paper cites.
Z. Zhang and B. Liu, “Research on key technologies for cross-cloud federated training of large language models,”
2024
Earlier work this paper cites.
R. Gafni, I. Aviv, and D. Haim, “Multi-party secured collaboration architecture from cloud to edge,”
2024
Earlier work this paper cites.
2024
Earlier work this paper cites.
Z. Ding, P. Li, Q. Yang, and S. Li, “Enhance image-to-image generation with llava-generated prompts,” in
2024
Earlier work this paper cites.
Q. Deng, Q. Yang, R. Yuan, Y. Huang, Y. Wang, X. Liu, Z. Tian, J. Pan, G. Zhang, H. Lin
2024
Earlier work this paper cites.
Y. Ji, Z. Li, R. Meng, S. Sivarajkumar, Y. Wang, Z. Yu, H. Ji, Y. Han, H. Zeng, and D. He, “RAG-RLRC-LaySum at BioLaySumm: Integrating retrieval-augmented generation and readability control for layman summarization of biomedical texts,” in
2024
Earlier work this paper cites.
H. Xu, X. Wang, and H. Chen, “Towards real-time and personalized code generation,” in
2024
Earlier work this paper cites.
Y. Ji, Z. Yu, and Y. Wang, “Assertion detection in clinical natural language processing using large language models,” in
2024
Earlier work this paper cites.
2024
Earlier work this paper cites.
2024
Cited alongside, same era.
D. Liu and Y. Yu, “MT2ST: Adaptive multi-task to single-task learning,”
2024
Cited alongside, same era.
Y. Ramaswamy, V. N. Sankaran, and B. K. M. Sundar, “Advanced cybersecurity strategies in cloud computing: Techniques for data protection and privacy,”
2024
Cited alongside, same era.
P. Li, M. Abouelenien, R. Mihalcea, Z. Ding, Q. Yang, and Y. Zhou, “Deception detection from linguistic and physiological data streams using bimodal convolutional neural networks,” in
2024
Cited alongside, same era.
P. Li, Q. Yang, X. Geng, W. Zhou, Z. Ding, and Y. Nian, “Exploring diverse methods in visual question answering,” in
R. Vadisetty and A. Polamarasetti, “AI-generated privacy-preserving protocols for cross-cloud data sharing and collaboration,” in
2024
Later among the works it cites.
D. K. Seth, K. K. Ratra, and A. P. Sundareswaran, “AI and generative AI-driven automation for multi-cloud and hybrid cloud architectures: Enhancing security, performance, and operational efficiency,” in
2025
Closest in time.
F. M. Rasel and B. Peter, “AI-driven frameworks for enhancing cybersecurity in multi-cloud environments,”
2025
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Y. Ji, W. Ma, S. Sivarajkumar, H. Zhang, E. M. Sadhu, Z. Li, X. Wu, S. Visweswaran, and Y. Wang, “Mitigating the risk of health inequity exacerbated by large language models,”
2025
Closest in time.
Q. Yi, Y. He, J. Wang, X. Song, S. Qian, M. Zhang
2025
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Z. Ding, Z. Lai, S. Li, P. Li, Q. Yang, and E. Wong, “Confidence trigger detection: Accelerating real-time tracking-by-detection systems,” in
2024
Cited alongside, same era.
T. Wang, Q. Yang, R. Wang, D. Sun, J. Li, Y. Chen, Y. Hu, C. Yang, T. Kimura, D. Kara
2024
Cited alongside, same era.
Z. Lin, W. Ma, T. Lin, Y. Zheng, J. Ge, J. Wang, J. Klein, T. Bissyande, Y. Liu, and L. Li, “Open-source AI-based se tools: Opportunities and challenges of collaborative software learning,”
2024
Cited alongside, same era.
K. Lazaros, D. E. Koumadorakis, A. G. Vrahatis, and S. Kotsiantis, “Federated learning: Navigating the landscape of collaborative intelligence,”
2024
Cited alongside, same era.
2024
Cited alongside, same era.
2024
Cited alongside, same era.
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Q. Yang, C. Ji, H. Luo, P. Li, and Z. Ding, “Data augmentation through random style replacement,”
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Y. Tao and A. Authors], “Flft: A large-scale pre-training model distributed fine-tuning method that integrates federated learning strategies,”
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