Welcome to 6G@HK
Advanced Technology (AT) Track 3: Wireless Networking Technology
Leader: Prof. Song GUO
Co-Leader: Prof. Qian ZHANG
Faculty Members: Prof. Khaled BEN LETAIEF, Prof. Vincent Kin Nang LAU, Prof. Kaibin HUANG, Prof. Jiaya JIA
Presentation by Prof. Song GUO on the progress of AT Track 3 during the mid-cycle review on-site visit on our 6G AoE Project in Oct 2024
Journal Papers (AT Track 3)
[1] Xiaoqi Wang, Hongyang Du, Yuehong Gao*, Jiayi Zhang, Dusit Niyato, and Khaled B. Letaief, “Secure Body-Centric Internet of Things Networks: Physical layer Security vs Covert Communication,” IEEE Transactions on Wireless Communications, Vol. 3, no. 10, pp. 12731-12748, Oct 2024. [paper]
[2] Quan Chen, Song Guo, Kaijia Wang, Wenchao Xu, Jing Li, Zhipeng Cai, Hong Gao, and Albert Zomaya, “Towards Real-Time Inference Offloading with Distributed Edge Computing: the Framework and Algorithms,” IEEE Transactions on Mobile Computing, Vol. 23, no. 7, pp. 7552-7571, Jul 2024. [paper]
[3] Jing Li, Song Guo, Weifa Liang, Jianping Wang, Quan Chen, Zichuan Xu, Wenzheng Xu, “AoI-Aware User Service Satisfaction Enhancement in Digital Twin-Empowered Edge Computing,” IEEE/ACM Transactions on Networking, Vol. 32, no. 2, pp. 1677-1690, Apr. 2024. [paper]
[4] Chuan Zhang, Xingqi Luo, Jinwen Liang, Ximeng Liu, Liehuang Zhu, and Song Guo, “POTA: Privacy-Preserving Online Multi-Task Assignment with Path Planning,”IEEE Transactions on Mobile Computing, Vol. 23, no. 5, pp. 5999-6011, May. 2024. [paper]
[5] Yuan Zeng, Yi Gong, Jiawei Liu, Shangao Lin, Zidong Han, Ruoxiao Cao, Kaibin Huang, Khaled Ben Letaief, “Multi-Channel Attentive Feature Fusion for Radio Frequency Fingerprinting,” IEEE Transactions on Wireless Communications, Vol. 23, no. 5, pp. 4243-4254, May 2024. [paper]
[6] Shijing Yuan, Beiyu Dong, Hongtao Lv, Hongze Liu, Hongyang Chen, Chentao Wu, Song Guo, Yue Ding, Jie Li, “Adaptive Incentivize for Cross-Silo Federated Learning in IIoT: A Multi-agent Reinforcement Learning Approach,” IEEE Internet of Things Journal, Vol. 11, no. 9, pp. 15048-15058, 01 May 2024. [paper]
[7] Xin Yuan, Ning Li, Tuo Zhang, Muqing Li, Yuwen Chen, Jose Fernan Martinez Ortega, and Song Guo, “High Efficiency Inference Accelerating Algorithm for NOMA-Based Edge Intelligence,” IEEE Transactions on Wireless Communications, Vol. 23, no. 11, pp. 17539-17556, Nov 2024. [paper]
[8] Xin Yuan, Ning Li, Kang Wei, Wenchao Xu, Quan Chen, Hao Chen, and Song Guo, “Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence,” IEEE Transactions on Mobile Computing, Vol. 24, no. 3, pp. 1530-1549, Mar 2025. [paper]
[9] Jixuan Cui, Jun Li, Zhen Mei, Kang Wei, Sha Wei, Ming Ding, Wen Chen, and Song Guo, “Federated Meta-Learning for Few-Shot Fault Diagnosis With Representation Encoding,” IEEE Transactions on Instrumentation and Measurement, Vol. 72, pp. 1-12, 30 Oct. 2023. [paper]
[10] Xin Yuan, Ning Li, Tuo Zhang, Muqing Li, Yuwen Chen, Jose Fernan Martinez Ortega, and Song Guo, “High Efficiency Inference Accelerating Algorithm for NOMA-based Mobile Edge Intelligence,” IEEE Transactions on Wireless Communications, Vol. 23, no. 11, pp. 17539-17556, Nov 2024. [paper]
[11] Xiaojia Wang, Suzhi Bi, Xian Li, Xiaohui Lin, Zhi Quan, and Ying-Jun Angela Zhang, “Capacity Analysis and Throughput Maximization of NOMA With Non-Linear Power Amplifier Distortion,” IEEE Transactions on Wireless Communications, Vol. 23, no. 12, pp. 18331-18345, Dec 2024. [paper]
[12] Jie Zhang, Song Guo, Xiaosong Ma, Wenchao Xu, Qihua Zhou, Jingcai Guo, Zicong Hong, and Jun Shan, “Model Decomposition and Reassembly for Purified Knowledge Transfer in Personalized Federated Learning,” IEEE Transactions on Mobile Computing, Vol. 24, no. 1, pp. 379-393, Jan 2025. [paper]
[13] Quan Chen, Song Guo, Wenchao Xu, Jing Li, Tuo Shi, Hong Gao, and Zhipeng Cai, “Average AoI Minimization With Directional Charging for Wireless-Powered Network Edge,” IEEE Transactions on Mobile Computing, Early Access, Jan 2025. [paper]
[14] Zhaolong Ning, Tengfeng Li, Yu Wu, Xiaojie Wang, Qingqing Wu, Fei Richard Yu, and Song Guo, “6G Communication New Paradigm: The Integration of Unmanned Aerial Vehicles and Intelligent Reflecting Surfaces,” IEEE Communications Surveys & Tutorials, Early Access, Jan 2025. [paper]
[15] Xin Yuan, Ning Li, Kang Wei, Wenchao Xu, Quan Chen, Hao Chen, and Song Guo, “Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence,” IEEE Transactions on Mobile Computing, Vol. 24, no. 3, pp. 1530-1549, Mar 2025. [paper]
[16] Yi Liu, Song Guo, Jie Zhang, Zicong Hong, Yufeng Zhan, and Qihua Zhou, “Collaborative Neural Architecture Search for Personalized Federated Learning,” IEEE Transactions on Computers, Vol. 74, no. 1, pp. 250-262, Jan 2025. [paper]
[17] Shijing Yuan, Qingshi Zhou, Jie Li, Song Guo, Hongyang Chen, Chentao Wu, and Yang Yang, “Adaptive Incentive and Resource Allocation for Blockchain-Supported Edge Video Streaming Systems: A Cooperative Learning Approach,” IEEE Transactions on Mobile Computing, Vol. 24, no. 2, pp. 539-556, Feb 2025. [paper]
[18] Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Song Guo, Yuguang Fang, and Dong In Kim, “Generative AI-Enabled Mobile Tactical Multimedia Networks: Distribution, Generation, and Perception,” IEEE Communications Magazine, Vol. 62, no. 10, pp. 96-102, Oct 2024. [paper]
[19] Jing Li, Song Guo, Weifa Liang, Jianping Wang, Quan Chen, Zicong Hong, Zichuan Xu, Wenzheng Xu, and Bin Xiao, “AoI-Aware Service Provisioning in Edge Computing for Digital Twin Network Slicing Requests,” IEEE Transactions on Mobile Computing, Vol. 23, no. 12, pp. 14607-14621, Dec 2024. [paper]
[20] Xiaojie Wang, Beibei Wang, Yu Wu, Zhaolong Ning, Song Guo, and Fei Richard Yu, “A Survey on Trustworthy Edge Intelligence: From Security and Reliability To Transparency and Sustainability,” IEEE Communications Surveys & Tutorials, Early Access, Aug 2024. [paper]
[21] Tao Guo, Song Guo, and Junxiao Wang, “Explore and Cure: Unveiling Sample Effectiveness With Context-Aware Federated Prompt Tuning,” IEEE Transactions on Mobile Computing, Vol. 23, no. 12, pp. 14044-14054, Dec 2024. [paper]
[22] Xiaoxin Su, Yipeng Zhou, Laizhong Cui, Quan Z. Sheng, Yinggui Wang, and Song Guo, “Fast-Convergent Wireless Federated Learning: A Voting-Based TopK Model Compression Approach,” IEEE Journal on Selected Areas in Communications, Vol. 42, no. 11, pp. 3048-3063, Nov 2024. [paper]
[23] Zhicheng Luo, Qianyi Huang, Xu Chen, Rui Wang, Fan Wu, Guihai Chen, and Qian Zhang, “Spectrum Sensing Everywhere: Wide-Band Spectrum Sensing With Low-Cost UWB Nodes,” IEEE/ACM Transactions on Networking, Vol. 32, no. 3, pp. 2112-2127, Jun 2024. [paper]
[24] Jinwen Liang, Song Guo, Zicong Hong, Enyuan Zhou, Chuan Zhang, Bin Xiao, “SecPQ: Secure Prediction Queries on Encrypted Outsourced Databases,” IEEE Transactions on Dependable and Secure Computing, Early Access, Mar 2025. [paper]
[25] Yi Liu, Song Guo, Jie Zhang, Yufeng Zhan, Qihua Zhou, Yingchun Wang, “Feature Correlation-Guided Knowledge Transfer for Federated Self-Supervised Learning,” IEEE Transactions on Neural Networks and Learning Systems, Early Access, Mar 2025. [paper]
[26] Gaochang Xie, Zehui Xiong, Renchao Xie, Xiumei Deng, Song Guo, Mohsen Guizani, and Zhu Han, “Mixture of Experts-Enabled Parallel Scheduling and Processing for Vehicular Generative AI Services,” IEEE Transactions on Cognitive Communications and Networking, Early Access, May 2025. [paper] 
[27] Shijing Yuan, Beiyu Dong, Jie Li, Song Guo, Hongyang Chen, Chentao Wu, Jie Wu, and Wei Zhao, “Adaptive Incentivize for Federated Learning With Cloud-Edge Collaboration Under Multi-Level Information Sharing,” IEEE Transactions on Computers, Vol. 74, no. 7, pp. 2445-2460, May 2025. [paper]
[28] Zhouxiang Zhao, Zhaohui Yang, Mingzhe Chen, Chen Zhu, Wei Xu, Zhaoyang Zhang, and Kaibin Huang, “Energy-Efficient Probabilistic Semantic Communication Over Space-Air-Ground Integrated Networks,” IEEE Transactions on Wireless Communications, Vol. 24, no. 10, pp. 8814-8829, Oct 2025. [paper]
[29] Xin Yuan, Ning Li, Quan Chen, Wenchao Xu, and Song Guo, “ERA: a QoE-Aware Collaborative Inference Algorithm for NOMA-based Edge Intelligence,” IEEE Transactions on Mobile Computing, Early Access, Sept 2025. [paper]
[30] Fahao Chen, Peng Li, Zicong Hong, Zhou Su, and Song Guo, “Communication-Efficient Sparsely-Activated Model Training via Sequence Migration and Token Condensation,” IEEE Transactions on Networking, Early Access, Jul 2025. [paper]
[31] Wanting Yang, Zehui Xiong, Song Guo, Shiwen Mao, Dong In Kim, and Merouane Debbah, “Efficient Multi-User Offloading of Personalized Diffusion Models: A DRL-Convex Hybrid Solution,” IEEE Transactions on Mobile Computing, Vol. 24, no. 9, pp. 9092-9109, Sept 2025. [paper]
[32] Jingyao Li, Pengguang Chen, Xuan Ju, Shu Liu, Hong Xu, and Jiaya Jia, “VLPose: Bridging the Domain Gap in Pose Estimation With Language-Vision Tuning,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 47, no. 11, pp. 10836-10847, Nov 2025. [paper]
[33] Tuo Zhang, Ning Li, Xin Yuan, Wenchao Xu, Quan Chen, Song Guo, Haijun Zhang,”Efficient Edge LLMs Deployment via HessianAware Quantization and CPU GPU Collaborative,” IEEE Transactions on Mobile Computing, Aug 2025. [paper]
[34] Enyuan Zhou, Song Guo, Zicong Hong, Christian S. Jensen, Yang Xiao, Jinwen Liang, and Dalin Zhang, “Pistis: A Decentralized Knowledge Graph Platform Enabling Ownership-Preserving SPARQL Querying,” Proceedings of the VLDB Endowment, Vol. 18, no. 11, pp. 4602-4615, Jul 2025. [paper]
[35] Ning Li, Song Guo, Tuo Zhang, Muqing Li, Zicong Hong, Qihua Zhou, Xin Yuan, and Haijun Zhang, “The MoE-Empowered Edge LLMs Deployment: Architecture, Challenges, and Opportunities,” IEEE Communications Magazine, Early Access, Aug 2025. [paper]
[36] Quan Chen, Zhipeng Cai, Jing Li, Ning Li, Lianglun Cheng, Hong Gao, and Song Guo, “Structure-Adaptive and Power-Aware Broadcast Scheduling for Multihop Wireless-Powered IoT Networks,” ACM Transactions on Sensor Networks, Vol. 21, Issue 1, Article No. 4, pp. 1 – 32, Jan 2025. [paper]
[37] Xin Yuan, Ning Li, Quan Chen, Wenchao Xu, and Song Guo, “ERA: a QoE-Aware Collaborative Inference Algorithm for NOMA-based Edge ,” IEEE Transactions on Mobile Computing, IEEE Transactions on Mobile Computing, Early Access, Sept 2025. [paper]
[38] Zhaolong Ning, Hao Hu, Xiaojie Wang, Lei Guo, Song Guo, Guoyin Wang, and Xinbo Gao, ACM Computing Surveys, “Mobile Edge Computing and Machine Learning in the Internet of Unmanned Aerial Vehicles: A Survey,” Vol. 56, Issue 1, Article No. 13, pp. 1-31, Aug 2023. [paper]
39
Conference Papers (AT Track 3)
[1] Fushuo Huo, Wenchao Xu, Song Guo, Jingcai Guo, HaozhaoWang, Ziming Liu, and Xiaocheng Lu, “ProCC: Progressive Cross-Primitive Compatibility for Open-World Compositional Zero-Shot Learning,” in Proc. Annual AAAI Conference on Artificial Intelligence, Vancouver, Canada, Feb. 2024. [paper]
[2] Yuechen Zhang, Shengju Qian, Bohao Peng, Shu Liu, and Jiaya Jia, “Prompt Highlighter: Interactive Control for Multi-Modal LLMs,” in Proc. IEEE / CVF Computer Vision and Pattern Recognition Conference, Seattle WA, United States, Jun. 2024. [paper]
[3] Xin Lai, Zhuotao Tian, Yukang Chen, Yanwei Li, Yuhui Yuan, Shu Liu, and Jiaya Jia, “LISA: Reasoning Segmentation via Large Language Model,” in Proc. IEEE / CVF Computer Vision and Pattern Recognition Conference, Seattle WA, United States, Jun. 2024. [paper]
[4] Shaoteng Liu, Yuechen Zhang, Wenbo Li, Zhe Lin, and Jiaya Jia, “Video-P2P: Video Editing with Cross-attention Control,” in Proc. IEEE / CVF Computer Vision and Pattern Recognition Conference, Seattle WA, United States, Jun. 2024. [paper]
[5] Sitong Wu, Haoru Tan, Zhuotao Tian, Yukang Chen, Xiaojuan Qi, and Jiaya Jia, “SaCo Loss: Sample-wise Affinity Consistency for Vision-Language Pre-training,” in Proc. IEEE / CVF Computer Vision and Pattern Recognition Conference, Seattle WA, United States, Jun. 2024. [paper]
[6] Yuechen Zhang, Jinbo Xing, Eric Lo, and Jiaya Jia, “Real-World Image Variation by Aligning Diffusion Inversion Chain,” in Proc. Conference on Neural Information Processing Systems (NeurIPS), New Orleans, United States, Dec. 2023. [paper]
[7] Xin Lai, Yuhui Yuan, Ruihang Chu, Yukang Chen, Han Hu, and Jiaya Jia, “Mask-Attention-Free Transformer for 3D Instance Segmentation,” in Proc. International Conference on Computer Vision (ICCV), Paris, France, Oct. 2023. [paper]
[8] Fanbin Lu, Xufeng Yao, Chi-Wing Fu, and Jiaya Jia, “Removing Anomalies as Noises for Industrial Defect Localization,” in Proc. International Conference on Computer Vision (ICCV), Paris, France, Oct. 2023. [paper]
[9] Sikai Bai, Jie Zhang, Song Guo, Shuaicheng Li, Jingcai Guo, Jun Hou, Tao Han, and Xiaocheng Lu, “DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning,” in Proc. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Jun 2024. [paper]
[10] Jinyu Chen, Wenchao Xu, Zicong Hong, Song Guo, Haozhao Wang, Jie Zhang, and Deze Zeng, “OTAS: An Elastic Transformer Serving System via Token Adaptation,” in Proc. IEEE INFOCOM 2024 – IEEE Conference on Computer Communications, Vancouver, BC, Canada, May 2024. [paper]
[11] Chonghe Zhao, Yipeng Zhou, Shengli Zhang, Taotao Wang, Quan Z. Sheng, and Song Guo, “DEthna: Accurate Ethereum Network Topology Discovery with Marked Transactions,” in Proc. IEEE INFOCOM 2024 – IEEE Conference on Computer Communications, Vancouver, BC, Canada, May 2024. [paper]
[12] Xiaoxin Su, Yipeng Zhou, Laizhong Cui, and Song Guo, “Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression,” in Proc. IEEE INFOCOM 2024 – IEEE Conference on Computer Communications, Vancouver, BC, Canada, May 2024. [paper]
[13] Yuxiao Ma, Wei Lou, and Song Guo, “On Securing Data Privacy in Federated Learning Using Noise-assisted Aggregated Multi-key Homomorphic Encryption,” in Proc. 2025 IEEE 45th International Conference on Distributed Computing Systems (ICDCS), in Proc. 2025 IEEE 45th International Conference on Distributed Computing Systems (ICDCS), Glasgow, United Kingdom, Jul 2025. [paper]
[14] Qianli Liu, Zicong Hong, Peng Li, Fahao Chen, and Song Guo, “Mell: Memory-Efficient Large Language Model Serving via Multi-GPU KV Cache Management,” in Proc. IEEE INFOCOM 2025 – IEEE Conference on Computer Communications, London, United Kingdom, May 2025. [paper]
[15] Bin Xia, Yuechen Zhang, Jingyao Li, Chengyao Wang, Yitong Wang, Xinglong Wu, Bei Yu, and Jiaya Jia, “DreamOmni: Unified Image Generation and Editing,” in Proc. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, Jun 2025. [paper]
[16] Senqiao Yang, Yukang Chen, Zhuotao Tian, Chengyao Wang, Jingyao Li, Bei Yu, and Jiaya Jia, “VisionZip: Longer is Better but Not Necessary in Vision Language Models,” in Proc. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, Jun 2025. [paper]
[17] Mingkang Zhu, Xi Chen, Zhongdao Wang, Hengshuang Zhao, and Jiaya Jia, “LogoSticker: Inserting Logos into Diffusion Models for Customized Generation,” in Proc. Computer Vision – ECCV 2024: 18th European Conference, Milan, Italy, Sept – Oct, 2024. [paper]
[18] Sitong Wu, Haoru Tan, Zhuotao Tian, Yukang Chen, Xiaojuan Qi, and Jiaya Jia, “SaCo Loss: Sample-Wise Affinity Consistency for Vision-Language Pre-Training,” in Proc. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Sept 2024. [paper]
[19] Yuechen Zhang, Shengju Qian, Bohao Peng, Shu Liu, and Jiaya Jia, “Prompt Highlighter: Interactive Control for Multi-Modal LLMs,” in Proc. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USAm Jun 2024. [paper]
[20] Xin Lai, Zhuotao Tian, Yukang Chen, Yanwei Li, Yuhui Yuan, Shu Liu, and Jiaya Jia, “LISA: Reasoning Segmentation via Large Language Model,” in Proc. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Jun 2024. [paper]
[21] Shaoteng Liu, Yuechen Zhang, Wenbo Li, Zhe Lin, and Jiaya Jia, “Video-P2P: Video Editing with Cross-Attention Control,” in Proc. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, Jun 2024. [paper]
[22] Xuan Liu, Siqi Cai, Qihua Zhou, Song Guo4, Ruibin Li, and Kaiwei Lin, “Mjölnir: Breaking the Shield of Perturbation-Protected Gradients via Adaptive Diffusion,” in Proc. The Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), Philadelphia, Pennsylvania, Mar 2025. [paper]
[23] Peiran Dong, Haowei Li, and Song Guo, “Durable Quantization Conditioned Misalignment Attack on Large Language Models,” in Proc. The International Conference on Learning Representations (ICLR) 2025, Singapore, Apr 2025. [paper]
[24] Akash Dhasade, Yaohong Ding, Song Guo, Anne-Marie Kermarrec, Martijn de Vos, and Leijie Wu, “QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation,” in Proc. MIDDLEWARE ’24: Proceedings of the 25th International Middleware Conference, Hong Kong, Dec 2024. [paper]
[25] Haodong Wang, Qihua Zhou, Zicong Hong, and Song Guo, “D2MoE: Dual Routing and Dynamic Scheduling for Efficient On-Device MoE-based LLM Serving,” in Proc. MobiCom 2025, Hong Kong, Nov 2025. [paper]
[26] Ruibin Li, Jingcai Guo, Qihua Zhou, and Song Guo, “FreePIH: Training-Free Painterly Image Harmonization with Diffusion Model,” in Proc. MM ’24: Proceedings of the 32nd ACM International Conference on Multimedia, Chengdu, China, Oct 2024. [paper]
[27] Yingchun Wang, Jingcai Guo, Song Guo, Yi Liu, Jie Zhang, and Weizhan Zhang, “SFP: Spurious Feature-Targeted Pruning for Out-of-Distribution Generalization,” in Proc. MM ’24: Proceedings of the 32nd ACM International Conference on Multimedia, Chengdu, China, Oct 2024. [paper]
[28] Jie Zhang, Xiaosong Ma, Song Guo, Peng Li, Wenchao Xu, Xueyang Tang, and Zicong Hong, “Amend to alignment: decoupled prompt tuning for mitigating spurious correlation in vision-language models,” in Proc. the 41st International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 2024. [paper]
[29] Xueyang Tang, Song Guo, Jingcai Guo, Jie Zhang, and Yue Yu, “Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization,” in Proc. the 41st International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 2024. [paper]
[30] Jiewei Zhang, Song Guo, Peiran Dong, Jie Zhang, Ziming Liu, Yue Yu, and Xiao-Ming Wu, “Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring,” in Proc. the 41st International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 2024. [paper]
[31] Fangqi Zhu, Hongtao Wu, Song Guo, Yuxiao Liu, Chilam Cheang, and Tao Kong, “IRASim: A Fine-Grained World Model for Robot Manipulation,” in Proc. International Conference on Computer Vision, ICCV 2025, Honolulu, Hawaii, Oct 2025. [paper]
[32] Zicong Hong, Jian Lin, Song Guo, Sifu Luo, Wuhui Chen, Roger Wattenhofer, and Yue Yu, “Optimus: Warming Serverless ML Inference via Inter-Function Model Transformation,” in Proc. the Nineteenth European Conference on Computer Systems (EuroSys ’24), Athens, Apr 2024. [paper]
[33] Sikai Bai, Shuaicheng Li, Weiming Zhuang, Jie Zhang, Kunlin Yang, Jun Hou, Shuai Zhang, Shuai Yi, and Junyu Gao, “Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators,” in Proc. The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, Feb 2024. [paper]
[34] Qihua Zhou, Jingcai Guo, Song Guo, Ruibin Li, Jie Zhang, BingjieWang, Zhenda Xu, “On the Robustness of Neural-Enhanced Video Streaming against Adversarial Attacks,” in Proc. The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, Feb 2024. [paper]
[35] Peiran Dong, Song Guo, and Junxiao Wang, “Investigating Trojan Attacks on Pre-trained Language Model-powered Database Middleware,” in Proc. KDD ’23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, California, USA, Aug 2023. [paper]
[36] Feijie Wu, Song Guo, Zhihao Qu, Shiqi He, Ziming Liu, and Jing Gao, “Anchor Sampling for Federated Learning with Partial Client Participation,” in Proc. the 40th International Conference on Machine Learning, Honolulu, Hawaii, Jul 2023. [paper]
[37] Zhisheng Zhong, Chengyao Wang, Yuqi Liu, Senqiao Yang, Longxiang Tang, Yuechen Zhang, Jingyao Li, Tianyuan Qu, Yanwei Li, Yukang Chen, Shaozuo Yu, Sitong Wu, Eric Lo, Shu Liu, and Jiaya Jia, “Lyra: An Efficient and Speech-Centric Framework for Omni-Cognition,” in Proc. International Conference on Computer Vision (ICCV 2025), Honolulu, Hawaii, Oct 2025. [paper]
[38] Sitong Wu, Haoru Tan, Yukang Chen, Shaofeng Zhang, Jingyao Li, Bei Yu, Xiaojuan Qi, and Jiaya Jia, “Mixture-of-Scores: Robust Image-Text Data Valuation via Three Lines of Code,” in Proc. the IEEE/CVF International Conference on Computer Vision (ICCV 2025), Honolulu, Hawaii, Oct 2025. [paper]
[39] Yuechen Zhang, Yaoyang Liu, Bin Xia, Bohao Peng, Zexin Yan, Eric Lo, and Jiaya Jia, “MagicMirror: ID-Preserved Video Generation in Video Diffusion Transformers,” in Proc. the IEEE/CVF International Conference on Computer Vision (ICCV 2025), Honolulu, Hawaii, Oct 2025. [paper]
[40] Pengguang Chen, Yukang Chen, Jianbo Dai, Zhijiang Guo, Jiaya Jia, Jingyao Li, Yinhong Liu, Jianqiao Lu, Zehan Qi, Linling Shen, Zhan Shi, Haochen Tan, Yingjia Wan, Bailin Wang, Rongwu Xu, Yuxuan Yao, Zhongshen Zeng, Hao Zhang, and Wanru Zhao, “MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs,” in Proc. Advances in Neural Information Processing Systems 37, Vancouver, Canada, Dec 2024. [paper]
[41] Yuechen Zhang, Jinbo Xing, BinXia, Shaoteng Liu, Bohao Peng, Xin Tao, Pengfei Wan, Eric Lo, and Jiaya Jia, “Training-Free Efficient Video Generation via Dynamic Token Carving,” in Proc. 39th Conference on Neural Information Processing Systems (NeurIPS2025), San Diego, USA, Dec 2025. [paper]
[42] Tianyuan Qu, Longxiang Tang, Bohao Peng, Senqiao Yang, BeiYu, and Jiaya Jia, “Does Your Vision-Language Model Get Lost in the Long Video Sampling Dilemma?,” in Proc. the IEEE/CVF International Conference on Computer Vision (ICCV 2025), Honolulu, Hawaii, Oct 2025. [paper]
[43] Bin Xia, Yuechen Zhang, Jingyao Li, Chengyao Wang, Yitong Wang, Xinglong Wu, Bei Yu, and Jiaya Jia, “DreamOmni: Unified Image Generation and Editing,” in Proc. The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2025, Nashville TN, USA, Jun 2025. [paper]
[44] Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang Chen, Shu Liu, Zongqing Lu, and Jiaya Jia, “RL-GPT: integrating reinforcement learning and code-as-policy,” in Proc. NIPS ’24: Proceedings of the 38th International Conference on Neural Information Processing Systems, Vancouver BC Canada, Dec 2024. [paper]
[45] Bin Xia, Shiyin Wang, Yingfan Tao, Yitong Wang, and Jiaya Jia, “LLMGA: Multimodal Large Language Model based Generation Assistant,” in Proc. The 18th European Conference on Computer Vision ECCV 2024, Milano, Italy, Sept-Oct 2024. [paper]
[46] Yanwei Li, Chengyao Wang, and Jiaya Jia, “LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models,” in Proc. The 18th European Conference on Computer Vision ECCV 2024, Milano, Italy, Sept-Oct 2024. [paper]
Posters (AT Track 3)
[1] “High Efficiency Inference Accelerating Algorithm for NOMA-based Edge Intelligence” (Prof. Song GUO’s group) 
[2] “Dynamic Air-Ground Networking and Clustering algorithms for High-Performance Edge Federated Learning” (Prof. Song GUO’s group)
[3] “Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence” (Prof. Song GUO’s group)
[4] “QoE and QoS based High Efficiency Inference Accelerating Algorithm for Edge Intelligence” (Prof. Song GUO’s group)
[5] “Empowering Mobile Devices with Multimodal Large Language Models in 6G Era” (Prof. Jiaya JIA’s group)