Publications

(* denotes correspondence) For the latest publications, please see my Google Scholar Profile.

Submitted/Preprints:

  1. R. Song, G.-H. Wang, Q.-G. Chen, W. Luo, T. Xu, Z. Liu, Y. Wang, Z. Lin, and J. Zhang, “Training-free image editing with visual context integration and concept alignment,” submitted. [arXiv]

  2. F. Lin, Y. Hu, L. Zhu, Z. Liu, Y. Huang, Z. Lin*, and J. Zhang, “Real-time human frontal view synthesis from a single image,” submitted. [arXiv] [Code]

  3. L. Zhu, Y. Huang, X. Ge, Y. Xue, Z. Liu, Y. Zhang, Z. Lin, and J. Zhang, “Flash-VAED: Plug-and-play VAE decoders for efficient video generation,” submitted. [arXiv] [Code]

  4. C. Wen, J. Tong, Z. Lin, C. Bian, and J. Zhang, “Bridging visual and wireless sensing: A unified radiation field for 3D radio map construction,” submitted. [arXiv] [Code]

  5. F. Lin, Y. Hu, Z. Liu, Y. Zhuang, Z. Lin*, and J. Zhang, “Mon3tr: Monocular 3D telepresence with pre-built Gaussian avatars as amortization,” submitted. [arXiv] [Project Page]

  6. Z. Liu, R. Song, Y. Huang, Y. Hu, X. Zhang, J. Shao, Z. Lin*, and J. Zhang, “Feed-forward 3D Gaussian splatting compression with long-context modeling,” submitted. [arXiv]

  7. Y. Hu, Y. He, J. Chen, W. Yuan, K. Qiu, Z. Lin, S. Zhu, Z. Dong, and J. Zhang, “Forge4D: Feed-forward 4D human reconstruction and interpolation from uncalibrated sparse-view videos,” submitted. [arXiv][Code][Project Page][Video]

  8. Z. Liu, Y. Hu, X. Zhang, J. Shao, Z. Lin*, and J. Zhang, “Dynamics-aware Gaussian splatting streaming towards fast on-the-fly training for 4D reconstruction,” submitted. [arXiv][Code][Project Page][Video]

  9. W. Sun, T. Li, Z. Lin, and J. Zhang, “Spatial-aware latent initialization for controllable image generation,” submitted. [arXiv]

Journal Articles

  1. J. Shao, Z. Li, W. Sun, T. Zhou, Y. Sun, L. Liu, Z. Lin, Y. Mao, and J. Zhang, “A survey of what to share in federated learning: Perspectives on model utility, privacy leakage, and communication efficiency,” to appear in ACM Computing Surveys. [arXiv][Wechat Official Accounts Article (Chinese)]

  2. C. Wen, J. Tong, Y. Hu, Z. Lin*, and J. Zhang, “Neural representation for wireless radiation field reconstruction: A 3D Gaussian splatting approach,” IEEE Transactions on Wireless Communications (TWC), vol. 25, pp. 7490-7504, 2026. [arXiv] [Code] [Wechat Official Accounts Article (Chinese)]

  3. J. Tong, J. Shao, Q. Wu, W. Guo, Z. Li, Z. Lin, and J. Zhang, “WirelessAgent: Large language model agents for intelligent wireless networks,” to appear in China Communications. [arXiv] [Code] [Video] [Wechat Official Accounts Article (Chinese)]

  4. T. Zhou, Z. Lin*, J. Zhang, and D. Tsang, “Understanding and improving model averaging in federated learning on heterogeneous data,” IEEE Transactions on Mobile Computing (TMC), vol. 23, no. 12, pp. 12131-12145, Dec. 2024. [arXiv][Code][Wechat Official Accounts Article (Chinese)]

  5. Z. Li, Z. Lin*, J. Shao, Y. Mao, and J. Zhang, “FedCiR: Client-invariant representation learning for federated non-IID features,” IEEE Transactions on Mobile Computing (TMC), vol. 23, no. 11, pp. 10509-10522, Nov. 2024. [arXiv]

  6. Y. Shen, J. Shao, X. Zhang, Z. Lin, H. Pan, D. Li, J. Zhang, and K. B. Letaief, “Large language models empowered autonomous edge AI for connected intelligence,” IEEE Communications Magazine, vol. 62, no. 10, pp. 140-146, Oct. 2024. [arXiv][Wechat Official Accounts Article (Chinese)]

  7. Y. Sun, Z. Lin*, Y. Mao, S. Jin, and J. Zhang, “Channel and gradient-importance aware device scheduling for over-the-air federated learning,” IEEE Transactions on Wireless Communications (TWC), vol. 23, no. 7, pp. 6905-6920, Jul. 2024. [arXiv]

  8. J. Shao, J. Tong, Q. Wu, W. Guo, Z. Li, Z. Lin, and J. Zhang, “WirelessLLM: Empowering large language models towards wireless intelligence,” Journal of Communications and Information Networks (Cover Paper), vol. 9, no. 2, pp. 99-112, Jun. 2024. (Cover Paper) [arXiv][Video][Wechat Official Accounts Article (Chinese)]

  9. Z. Lin, H. Liu, and Y.-J. A. Zhang, “CFLIT: Coexisting federated learning and information transfer,” IEEE Transactions on Wireless Communications (TWC), vol. 22, no. 11, pp. 8436–8453, Nov. 2023. [arXiv]

  10. H. Liu, Z. Lin, X. Yuan, and Y.-J. A. Zhang, “Reconfigurable intelligent surface empowered over-the-air federated edge learning,” IEEE Wireless Communications, vol. 30, no. 6, pp. 111-118, Dec. 2023. [arXiv]

  11. Z. Lin, H. Liu, and Y.-J. A. Zhang, “Relay-assisted cooperative federated learning,” IEEE Transactions on Wireless Communications (TWC), vol. 21, no. 9, pp. 7148–7164, Sept. 2022. [arXiv] [Code]

  12. Z. Lin, S. Bi, and Y.-J. A. Zhang, “Optimizing AI service placement and resource allocation in mobile edge intelligence systems,” IEEE Transactions on Wireless Communications (TWC), vol. 20, no. 11, pp. 7257-7271, Nov. 2021. [arXiv]

  13. Z. Lin and Y. Liu, “Joint uplink and downlink transmissions in user-centric OFDMA cloud-RAN,” IEEE Transactions on Vehicular Technology (TVT), vol. 68, no. 8, pp. 7776-7788, Aug. 2019. [arXiv]

Conference Papers

  1. Y. Li, Z. Liu, Z. Li, Z. Lin*, and J. Zhang, “RemedyGS: Defend 3D Gaussian splatting against computation cost attacks,” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Denver, Colorado, USA, June 2026. [arXiv] [Code]

  2. Y. Li, Z. Liu, Z. Li, Z. Lin*, and J. Zhang, “Token-level data selection for safe LLM fine-tuning,” International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, April 2026. [Paper] [arXiv] [Code]

  3. R. Song, Y. Wang, T. Xu, Z. Liu, Z. Lin*, and J. Zhang, “Low-latency neural LiDAR compression with 2D context models,” International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, April 2026. [Paper] [Code]

  4. J. Bao, H. Chen, L. Zhu, C. Liu, R. Zhang, K. Luo, Z. Hu, W. Chen, Y. Yin, X. Wang, Z. Lin*, J. Zhang, and X. Han, “LumiTex: Towards high-fidelity PBR texture generation with illumination context,” International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, April 2026. [arXiv][Code][Project Page]

  5. Y. Hu, Z. Liu, J. Shao, Z. Lin*, and J. Zhang, “EVA-Gaussian: 3D Gaussian-based real-time human novel view synthesis under diverse camera settings,” International Workshop on End-to-End 3D Learning (E2E3D) in Conjunction with ICCV 2025, Honolulu, Hawaii, USA, October 2025. [arXiv][Code][Project Page]

  6. X. Zhang, Z. Liu, Y. Zhang, X. Ge, D. He, T. Xu, Y. Wang, Z. Lin, S. Yan, and J. Zhang, “MEGA: Memory-efficient 4D Gaussian splatting for dynamic scenes,” IEEE/CVF International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, October 2025. (Highlight) [arXiv][Code][Project Page]

  7. H. Chen, Z. Lin*, and J. Zhang, “GI-GS: Global illumination decomposition on Gaussian splatting for inverse rendering,” International Conference on Learning Representations (ICLR), Singapore, April 2025. [arXiv][Code][Project Page] [Wechat Official Accounts Article (Chinese)]

  8. C. Wen, J. Tong, Y. Hu, Z. Lin*, and J. Zhang, “WRF-GS: Wireless radiation field reconstruction with 3D Gaussian splatting,” IEEE International Conference on Computer Communications (INFOCOM), London, United Kingdom, May 2025. [arXiv] [Code] [Wechat Official Accounts Article (Chinese)]

  9. Z. Liu, X. Zhang, J. Shao, Z. Lin*, and J. Zhang, “Bidirectional stereo image compression with cross-dimensional entropy model,” European Conference on Computer Vision (ECCV), Milano, Italy, Sept.-Oct. 2024. [arXiv] [Code] [Video][Wechat Official Accounts Article (Chinese)]

  10. Y. Sun, Z. Lin*, Y. Mao, S. Jin, and J. Zhang, “Probabilistic scheduling for over-the-air federated learning,” IEEE International Conference on Communication Technology (ICCT), Wuxi, China, Oct. 2023.

  11. Z. Lin, H. Liu, and Y.-J. A. Zhang, “Relay-assisted over-the-air federated learning,” IEEE Global Communications Conference Workshops (GLOBECOM Wkshps), Madrid, Spain, Dec. 2021.

  12. Z. Lin, S. Bi, and Y.-J. A. Zhang, “Optimizing AI service placement and computation offloading in mobile edge intelligence systems,” IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, Dec. 2020.

  13. Z. Lin and Y. Liu, “Joint uplink-downlink resource allocation in OFDMA cloud radio access networks,” IEEE International Conference on Communications (ICC), Kansas City, MO, USA, May 2018.

  14. Z. Lin and Y. Liu, “User-centric OFDMA cloud radio access networks with fronthaul capacity constraints,” IEEE Global Communications Conference (GLOBECOM), Singapore, Dec. 2017.