Publications

Preprints

• • E. Bao, and L. Song, "Equivariant neural networks and equivarification." arXiv preprint arXiv:1906.07172, 2019.

  • L. Song, C. Fragouli, and D. Shah, "Regret vs. broadcast transmissions over wireless recommendation systems," arXiv:1810.06313.

Journal Papers

[77] Sichun Luo, Jian Xu, Xiaojie Zhang, Linrong Wang, Sicong Liu, Hanxu Hou, and Linqi Song, "RALLRec+：Retrieval augmented large language model recommendation with reasoning," Expert Systems With Applications, early access, 2025.

[76] Shuli Luo, Sylvia He, Linqi Song, and Sisi Jian, "Exploring the potential of large language models (LLMs) in analyzing passengers' perceptions of transit service quality," Environment and Planning B: Urban Analytics and City Science, early access, 2025. 

[75] Qianfan Wang, Yiwen Wang, Jifan Liang, Linqi Song, and Xiao Ma, "A two-stage soft-decision decoding algorithm for BCH codes," IEEE Transactions on Communications, early access, 2025.

[74] Xiaojie Zhang, Guoting Chen, Linqi Song, and Wensheng Gan, "Short-sighted knowledge discovery in temporal transaction database via time pruning," Knowledge-Based Systems, vol. 325, pp. 113996, 2025. 

[73] Mingying Xu, Kui Peng, Jie Liu, Qing Zhang, Linqi Song, and Yinqiao Li, "Multimodal Named Entity Recognition based on topic prompt and multi-curriculum denoising," Information Fusion, pp. 103405, 2025. 

[72] Bin Yu, Zhengyi Jiang, Zhongyi Huang, Linqi Song, and Hanxu Hou, "Explicit constructions of rack-aware regenerating codes for multi-node failures," IEEE Transactions on Communications, early access, 2025.

[71] Tan Li and Linqi Song, "Client association and resource allocation for NOMA-enabled hierarchical federated learning with non-IID data," IEEE Transactions on Network Science and Engineering, early access, 2025.

[70] Yuxuan Yao, Mingyang Liu, Guanzhi Deng, Zengyan Liu, Dapeng Wu, Han Wu, and Linqi Song, "Leveraging correctness-based learning for efficient reasoning via automated process supervision," IEEE Journal of Selected Topics in Signal Processing, early access, 2025.

[69] Jifan Liang, Qianfan Wang, Lvzhou Li, Linqi Song, and Xiao Ma, "A low-complexity BP-OSD algorithm for quantum LDPC codes," The European Physical Journal Special Topics, 2025.

[68] Shuqi Liu, Bowei He, Chen Ma, and Linqi Song, "Reasoning in action: MCTS-driven knowledge retrieval for large language models," IEEE Journal of Selected Topics in Signal Processing, early access, 2025.

[67] Xiangqun Zhang, Ruize Han, Likai Wang, Linqi Song, Junhui Hou, and Wei Feng, "Synthetic-to-real video person re-ID," IEEE Transactions on Information Forensics and Security, 2025.

[66] Sichun Luo, Bowei He, Haohan Zhao, Wei Shao, Yanlin Qi, Yinya Huang, Aojun Zhou, Yuxuan Yao, Zongpeng Li, Yuanzhang Xiao, Mingjie Zhan, and Linqi Song, "RecRanker: Instruction tuning large language model as ranker for top-k recommendation," ACM Transactions on Information Systems, 2024.

[65] Xiaojie Zhang, Guoting Chen, Linqi Song, and Wensheng Gan, "Skyline recency–frequency–monetary pattern mining based on different constraint degrees," Engineering Applications of Artificial Intelligence, vol. 149, 2025.

[64] Jiong Wang, Qing Zhang, Jie Liu, Kaifeng Nie, Ze Zhang, Linqi Song, and Yinqiao Li, "Sub-network knowledge injection and transferable parameter updating strategy for continual learning of vision-and-language tasks," IEEE Transactions on Artificial Intelligence, 2025.

[63] Guangfeng Yan, Tan Li, Kui Wu, and Linqi Song, "Layered randomized quantization for communication-efficient and privacy-preserving distributed learning," IEEE Journal on Selected Areas in Communications, 2025.

[62] Xiaoming Xue, Cuie Yang, Liang Feng, Kai Zhang, Linqi Song, and Kay Chen Tan, "A scalable test problem generator for sequential transfer optimization," IEEE Transactions on Cybernetics, vol. 55, no. 5, pp. 2110 - 2123, 2025.

[61] Xiaojie Zhang, Guoting Chen, Linqi Song, and Wensheng Gan, "Enabling knowledge discovery through low utility itemset mining," Expert Systems with Applications, vol. 265, 2025.

[60] Kang Zhou, Jianping Wang, Weitao Xu, Linqi Song, Zaiqiao Ye, Chi Guo, and Cong Li, "Learning and grounding visual multimodal adaptive graph for visual navigation," Information Fusion, vol. 118, 2025.

[59] Zhengyi Jiang, Hao Shi, Zhongyi Huang, Linqi Song, Bo Bai, Gong Zhang, and Hanxu Hou, "Error correction decoding algorithms of RS codes based on an earlier termination algorithm to find the error locator polynomial," IEEE Transactions on Information Theory, 2025.

[58] Sicong Liu, Xiao Tang, and Linqi Song, "Massive random access control for VLC: A reinforcement learning driven approach," IEEE Photonics Technology Letters, 2025.

[57] Xiaoming Xue, Yao Hu, Liang Feng, Kai Zhang, Linqi Song, and Kay Chen Tan. "Surrogate-assisted search with competitive knowledge transfer for expensive optimization," IEEE Transactions on Evolutionary Computation, 2024.

[56] Zhiping Xu, Deyin Xu, Lixiong Lin, Linqi Song, Dan Song, Yanglong Sun, and Qiwang Chen, "Integrated object detection and communication for synthetic aperture radar images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 294-307, 2025.

[55] Jian Xu, Shuo Wan, Yinchuan Li, Sichun Luo, Zhilin Chen, Yunfeng Shao, Zhitang Chen, Shao-Lun Huang, and Linqi Song, "Cooperative Multi-Model Training for Personalized Federated Learning over Heterogeneous Devices." IEEE Journal of Selected Topics in Signal Processing, vol. 19, no. 1, pp. 195-207, 2025.

[54] Zerui Yang, Wei Shao, Yudai Matsuda, Linqi Song, “iResNetDM: An interpretable deep learning approach for four types of DNA methylation modification prediction,” Computational and Structural Biotechnology Journal, vol. 23, pp. 4214-4221, 2024.

[53]  Lintai Wu, Junhui Hou, Linqi Song, and Yong Xu, "3D shape completion on unseen categories: A weakly-supervised approach,"  IEEE Transactions on Visualization and Computer Graphics, early access, 2024.

[52]  Rina Su, Qifu Tyler Sun, Le Wang, Shaoteng Liu, Zhongshan Zhang, and Linqi Song, "Lightweight instantly decodable network coding: Performance analysis and algorithm design,"  IEEE Transactions on Communications, early access, 2024.

[51] Huanqi Yang, Di Duan, Hongbo Liu, Chengwen Luo, Yuezhong Wu, Wei Li, Albert Y. Zomaya, Linqi Song, and Weitao Xu, "Scenario-adaptive key establishment scheme for LoRa-enabled IoV communications," IEEE Transactions on Mobile Computing, early access, 2024.

[50] Shuqi Liu, Han Wu, Guanzhi Deng, Jianshu Chen, Xiaoyang Wang, and Linqi Song, "Towards improving interpretability of language model generation through a structured knowledge discovery approach," IEEE Journal of Selected Topics in Signal Processing, early access, 2024.

[49] Sichun Luo, Yuanzhang Xiao, Xinyi Zhang, Yang Liu, Wenbo Ding, and Linqi Song, "PerFedRec++: Enhancing personalized federated recommendation with self-supervised pre-training,"  ACM Transactions on Intelligent Systems and Technology, early access, 2024.

[48] Xiaoming Xue, Cuie Yang, Liang Feng, Kai Zhang, Linqi Song, and Kay Chen Tan, "Solution transfer in evolutionary optimization: an empirical study on sequential transfer," in IEEE Transactions on Evolutionary Computation, early access, 2023.

[47] Chenming Cao, Xiaoming Xue, Linqi Song, Liming Zhang, Xia Yan, Yongfei Yang, Jun Yao, Jian Wang, and Kai Zhang, "Competitive knowledge transfer-enhanced surrogate-assisted search for production optimization," SPE Journal, vol. 29, no. 06, pp. 3277–3292, 2024.

[46] Mengzhe Ruan, Guangfeng Yan, Yuanzhang Xiao, Linqi Song, and Weitao Xu, "Adaptive top-k in SGD for communication-efficient distributed learning in multi-robot collaboration," IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 3, pp. 487-501, 2024.

[45] Sichun Luo, Yuxuan Yao, Haohan Zhao, and Linqi Song, "A language model-based fine-grained address resolution framework in UAV delivery system," IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 3, pp. 529-539, 2024.

[44] Hanwei Zhu, Baoliang Chen, Lingyu Zhu, Peilin Chen, Linqi Song, and Shiqi Wang, "Video quality assessment for spatio-temporal resolution adaptive coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 7, pp. 6403-6415, 2024.

[43] Letian Zhang, Zhuo Lu, Linqi Song, and Jie Xu, "CrossVision: real-time on-camera video analysis via common RoI load balancing", IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 5027-5039, 2024.

[42] Baoliang Chen, Lingyu Zhu, Hanwei Zhu, Wenhan Yang, Linqi Song, and Shiqi Wang, "Gap-closing matters: Perceptual quality evaluation and optimization of low-light image enhancement", IEEE Transactions on Multimedia, vol. 26, pp. 3430-3443, 2024.

[41] Guangfeng Yan, Tan Li, Kun Wu, and Linqi Song, "Killing two birds with one stone: Quantization achieves privacy in distributed learning," Digital Signal Processing, vol. 146, pp. 104353, 2023.

[40] Han Wu, Kun Xu, and Linqi Song, "Structure-aware dialogue modeling methods for conversational semantic role labeling," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 742-752, 2023.

[39] Xiaojie Zhang, Guoting Chen, Linqi Song, Wensheng Gan, and Yunling Song. "HEPM: High-efficiency pattern mining." Knowledge-Based Systems, vol. 281, no. C, pp. 111068, 2023.

[38] Rucheng Wu, Wenbo Ding, Xiaomin Xu, Linqi Song, and Weitao Xu, "Gesture recognition based on flexible solar cells and ultrathin hydrogel film",  Telecommunications Science, vol. 39, no. 7, pp. 109-115, 2023.

[37] Yao Hu, Zhi-An Huang, Rui Liu, Xiaoming Xue, Xiaoyan Sun, Linqi Song, Kay Chen Tan, "Source free semi-supervised transfer learning for diagnosis of mental disorders on fMRI scans", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 11, 2023.

[36] Han Sun, Wei Shao, Tao Li, Jiayu Zhao, Weitao Xu, Linqi Song, "A pruning-then-quantization model compression framework for facial emotion recognition," Intelligent and Converged Networks, vol. 4, no. 3, pp. 225-236, 2023.

[35] Keqi Song, Tao Ni, Linqi Song, and Weitao Xu, "Emma: An accurate, efficient, and multi-modality strategy for autonomous vehicle angle prediction." Intelligent and Converged Networks, vol. 4, no. 1, pp. 41-49, 2023.

[34] Mengwei Yang, Shuqi Liu, Jie Xu, Guozhen Tan, Congduan Li, and Linqi Song, "Achieving privacy-preserving cross-silo anomaly detection using federated XGBoost," Journal of The Franklin Institute, vol. 360, no. 9, pp. 6194-6210, 2023.

[33] Tan Li and Linqi Song, "Federated online learning aided multi-objective proactive caching in heterogeneous edge networks," IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 4, pp. 1080-1095, 2023.

[32] Zihao Zhao, Yuzhu Mao, Yang Liu, Linqi Song, Ye Ouyang, Xinlei Chen, and Wenbo Ding, "Towards efficient communications in federated learning: a contemporary survey," Journal of the Franklin Institute, vol. 360, no. 12, pp. 8669-8703, 2023. 

[31] Shuli Luo, Sylvia Y. He, Susan Grant-Muller, and Linqi Song, "Influential factors in customer satisfaction of transit services: Using crowdsourced data to reveal the heterogeneity across individuals, space and time," Transport Policy, vol. 131, pp. 173-183, 2023. 

[30] Zhi-An Huang, Yao Hu, Rui Liu, Xiaoming Xue, Zexuan Zhu, Linqi Song, Kay Chen Tan, "Federated multi-task learning for joint diagnosis of multiple mental disorders on MRI scans," IEEE Transactions on Biomedical Engineering, vol. 70, no. 4, pp. 1137-1149, 2023. 

[29] Yao Hu, Xiaoyan Sun, Ye Tian, Linqi Song, and Kay Chen Tan, "Communication efficient federated learning with heterogeneous structured client models," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 3, pp. 753-767, 2023. 

[28] Guangfeng Yan, Tan Li, Shao-Lun Huang, Tian Lan, and Linqi Song, "AC-SGD: Adaptively compressed SGD for communication-efficient distributed learning," IEEE Journal on Selected Areas in Communications, vol. 40, no. 9, pp. 2678-2693, 2022. 

[27] Xiaoming Xue, Guodong Chen, Kai Zhang, Liming Zhang, Xinggang Zhao, Linqi Song, Menghan Wang, and Peng Wang, "A divide-and-conquer optimization paradigm for waterflooding production optimization," Journal of Petroleum Science and Engineering, vol. 211, 2022.

[26]  Yuzhu Mao, Zihao Zhao, Guangfeng Yan, Yang Liu, Tian Lan, Linqi Song, and Wenbo Ding, "Communication efficient federated learning with adaptive quantization," IEEE Transactions on Intelligent Systems and Technology, vol. 13, no. 4, 2022.

[25] Tan Li and Linqi Song, "Privacy-preserving communication-efficient federated multi-armed bandits," IEEE Journal on Selected Areas in Communications, vol. 40, no. 3, pp. 773-787, 2022.

[24] Xiaoming Xue, Cuie Yang, Yao Hu, Kai Zhang, Yiu-ming Cheung, Linqi Song, and Kay Chen Tan, "Evolutionary sequential transfer optimization for objective-heterogeneous problems," IEEE Transactions on Evolutionary Computation, vol. 26, no. 6, pp. 1424-1438, 2022.

[23] Lei Huang, Jiecong Lin, Xiangtao Li, Linqi Song, Ka-Chun Wong, "EGFI: Drug-drug interaction extraction and generation with fusion of enriched entity and sentence information" Briefings in Bioinformatics, vol. 23, no. 1, 2022.

[22] Shuqi Liu, Wei Shao, Tan Li, Weitao Xu, and Linqi Song, "Recent advances in biometrics-based user authentication for wearable devices: A contemporary survey," Digital Signal Processing, vol. 125, 2022. 

[21] Wei Shao, Bolin Hua, and Linqi Song, "A pattern and POS auto-learning method for terminology extraction from scientific text," Data and Information Management, vol. 5, no. 3, 2021.

[20] Tan Li, Yuanzhang Xiao, Linqi Song, "Integrating future smart home operation platform with demand side management via deep reinforcement learning," IEEE Transactions on Green Communications and Networking, vol. 5, no. 2, 2021.

[19] Kun Xu, Han Wu, Linfeng Song, Haisong Zhang, Linqi Song and Dong Yu, "Conversational semantic role labeling," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 2465 - 2475, 2021.

[18] Mianlong Chen, Kui Wu and Linqi Song, "A Whittle index approach to minimizing age of multi-packet information in IoT network," in IEEE Access, vol. 9, pp. 31467-31480, 2021.

[17] Deepesh Data, Linqi Song, and Suhas Diggavi, "Data encoding for Byzantine-resilient distributed optimization," IEEE Transactions on Information Theory, vol. 67, no. 2, pp. 1117-1140, 2021.

[16] Tan Li, Congduan Li, Jingjing Luo, and Linqi Song, "Wireless recommendations for internet of vehicles: Recent advances, challenges, and opportunities," Intelligent and Converged Networks, vol. 1, no. 1, pp. 1-17, 2020. (First paper in the first issue!)

[15] T. Zhao, S. Zhou, L. Song, Z. Jiang, X. Guo, and Z. Niu, "Energy-optimal and delay-bounded computation offloading in mobile edge computing with heterogeneous clouds," China Communications, vol. 17, no. 5, pp. 191-210, 2020.

[14] Y. Bai, L. Chen, L. Song, and J. Xu, "Risk-aware edge computation offloading using Bayesian Stackelberg game," IEEE Transactions on Network and Service Management, vol. 17, no. 2, 2020.

[13] H. Tang, J. Wang, L. Song, and J. Song, "Minimizing age of information with power constraints: Multi-user opportunistic scheduling in multi-state time-varying channels," IEEE Journal on Selected Areas in Communications, vol. 38, no. 5, pp. 854-868, 2020.

[12] L. Chen, L. Song, J. Chakareski, and J. Xu, "Collaborative Content Placement among Wireless Edge Caching Stations with Time-to-Live Cache," IEEE Transactions on Multimedia, vol. 22, no. 2, pp. 432-444, 2020.

[11] M. Karmoose, L. Song, M. Cardone, and C. Fragouli, "Privacy in index coding: k-limited-access schemes," IEEE Transactions on Information Theory, vol. 66, no. 5, pp. 2625-2641, 2019.

[10] L. Song, and C. Fragouli, T. Zhao, "A pliable index coding approach to data shuffling," IEEE Transactions on Information Theory, vol. 66, no. 3, pp. 1333-1353, 2019.

[9] L. Song, and C. Fragouli, “Making recommendations bandwidth aware,” IEEE Transactions on Information Theory, vol. 64, no. 11, pp. 7031-7050, 2018. 

[8] L. Song, and C. Fragouli, “A polynomial-time algorithm for pliable index coding,” IEEE Transactions on Information Theory, vol. 64, no. 2, pp. 979-999, 2018.

[7] J. Xu, L. Song, J. Y. Xu, G. J. Pottie and M. van der Schaar, “Personalized active learning for activity classification using wireless wearable sensors,” in IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 5, pp. 865-876, Aug. 2016.

[6] L. Song, C. Tekin and M. van der Schaar, “Online learning in large-scale contextual recommender systems,” in IEEE Transactions on Services Computing, vol. 9, no. 3, pp. 433-445, May-June, 2016.

[5] L. Song, W. Hsu, J. Xu and M. van der Schaar, “Using contextual learning to improve diagnostic accuracy: application in breast cancer screening,” in IEEE Journal of Biomedical and Health Informatics, vol. 20, no. 3, pp. 902-914, May 2016.

[4] L. Song, Y. Xiao, and M. van der Schaar, “Demand side management in smart grids using a repeated game framework,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 7, 2014.

[3] L. Zhang, L. Song, Q. Xie, and J. Wang, “Design of soft-in-soft-out decoder of NR code in DTMB national standard system,” Video Engineering, vol. 33, no. 3, 2009.

[2] L. Song, and J. Wang, “Demapping method in DTMB system,” Video Engineering, vol. 32, no. 6, 2008.

[1] L. Song, J. Wang, and C. Pan, “Design and implementation of convolutional de-interleaver in DTMB system,” Video Engineering, vol. 32, no. 1, 2008.

Conference Papers

[114] Gangwei Jiang, Yahui Liu, Zhaoyi Li, V. W., Fuzheng Zhang, Linqi Song, Ying Wei, and Defu Lian, "What makes a good reasoning chain? Uncovering structural patterns in long chain-of-thought reasoning," in Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.

[113] Qianfan Wang, Yiwen Wang, Jifan Liang, Linqi Song, and Xiao Ma, "A maximum-likelihood decoding of BCH codes," in 2025 Asia Pacific Workshop on Data Science and Information Theory (APWDSIT), 2025.

[112] Yiwen Wang, Qianfan Wang, Xiangping Zheng, Linqi Song, and Xiao Ma, "Reduced-complexity guessing codeword decoding of BCH codes with most reliable cyclic basis," in IEEE Global Communications Conference (GlobeCom), 2025.

[111] Qianfan Wang, Yiwen Wang, Jiayi Yang, Linqi Song, and Xiao Ma, "Low-complexity BP-ORBOSD algorithm for short 5G LDPC codes," 2025 IEEE/CIC International Conference on Communications in China - Workshop: Coding and Signal Processing for Real-Time Communications  (ICCC Workshops), 2025.

[110] Zekun Qian, Ruize Han, Junhui Hou, Linqi Song, and Wei Feng, "VOVTrack: Exploring the potentiality in raw videos for open-vocabulary multi-object tracking," International Conference on Computer Vision (ICCV), 2025. 

[109] Zerui Yang, Yinqiao Li, Yudai Matsuda, and Linqi Song, "HMG-DTI: A drug-target interaction prediction framework combining hierarchical molecular graphs and improved convolutional block attention module," Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025.

[108] Shuqi Liu, Han Wu, Bowei He, Xiongwei Han, Mingxuan Yuan, and Linqi Song, "Sens-merging: Sensitivity-guided parameter balancing for merging large language models," in Annual Meeting of the Association for Computational Linguistics (ACL) (findings), 2025.

[107] Jian Xu, Sichun Luo, Xiangyu Chen, Haoming Huang, and Linqi Song, "Rec-RAG: Improving Retrieval Augmented Large Language Model Recommendation with Representation Learning," in The Web Conference (WWW), 2025.

[106] Wei Shao, Mingyang Liu, and Linqi Song, "DiffETM: Diffusion process enhanced embedded topic model," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.

[105] Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, and Jing Tang, "OptiBench meets ReSocratic: Measure and improve LLMs for optimization modeling,"  in The Thirteenth International Conference on Learning Representations (ICLR), 2025.

[104] Yuxuan Yao, Han Wu, Mingyang Liu, Sichun Luo, Xiongwei Han, Jie Liu, Zhijiang Guo, and Linqi Song, "Determine-then-ensemble: necessity of top-k union for large language model ensembling," in The Thirteenth International Conference on Learning Representations (ICLR), 2025.

[103] Gangwei Jiang, Caigao JIANG, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, and Ying Wei, "Unlocking the power of function vectors for characterizing and mitigating catastrophic forgetting in continual instruction tuning," in The Thirteenth International Conference on Learning Representations (ICLR), 2025.

[102] Le Wang, Rina Su, Qifu Tyler Sun, Shaoteng Liu, Zhongshan Zhang, and Linqi Song, "Lightweight instantly decodable network coding in wireless broadcast," In 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), pp. 1-7, 2024.

[101] Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, and Ying Wei, "Duquant: Distributing outliers via dual transformation makes stronger quantized LLMs." Advances in Neural Information Processing Systems 37 (NeurIPS), pp. 87766-87800, 2024.

[100] Xiaohan Lin, Qingxing Cao, Yinya Huang, Haiming Wang, Jianqiao Lu, Zhengying Liu, Linqi Song, and Xiaodan Liang, "FVEL: Interactive formal verification environment with large language models via theorem proving." Advances in Neural Information Processing Systems 37 (NeurIPS), pp. 54932-54946, 2024.

[99] Tan Li, Yanming Gong, Hai Liu, Zhen Chen, and Linqi Song. "Communication-efficient multi-modal federated learning via dynamic client-modality matching," in 2024 IEEE International Conference on Big Data (BigData), pp. 7899-7908, 2024.

[98] Weichuan Wang, Zhaoyi Li, Defu Lian, Chen Ma, Linqi Song, and Ying Wei, "Mitigating the language mismatch and repetition issues in LLM-based machine translation via model editing," in Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 15681-15700. 2024.

[97] Yinqiao Li, Linqi Song, and Hanxu Hou, "LoRAN: Improved low-rank adaptation by a non-linear transformation," in Findings of the Association for Computational Linguistics (EMNLP), pp. 3134-3143, 2024.

[96] Zebing Lin, Jingjie Lv, Pingping Li, Linqi Song, Hui Liang, and Hanxu Hou, "Fast erasure decoding algorithm for Reed-Solomon codes based on decomposition of Vandermonde matrix,"  in International Conference on Wireless Communications and Signal Processing (WCSP), 2024.

[95] Yupeng Zhang, Shuqi Zheng, Ruize Han, Yuzhong Feng, Junhui Hou, Linqi Song, Wei Feng, and Liang Wan, "Rethinking the one-shot object detection: cross-domain object search," in ACM Multimedia (ACMMM), 2024.

[94] Mengzhe. Ruan, Yunhe Li, Weizhou Zhang, Linqi Song, and Weitao Xu, "Optimal power control for over-the-air federated learning with gradient compression," in Proceedings of the 30th International Conference on Parallel and Distributed Systems (ICPADS), Belgrade, Serbia, 2024.

[93] Guangfeng Yan, Shanxiang Lyu, Hanxu Hou, Zhiyong Zheng, and Linqi Song, "Towards quantum-safe distributed learning via homomorphic encryption: learning with gradients," in IEEE Information Theory Workshop, 2024.

[92] Wenhao Liu, Zhengyi Jiang, Zhongyi Huang, Linqi Song, and Hanxu Hou, "On the I/O cost of linear repair schemes for arbitrary $(n, k)$ Reed-Solomon codes," in IEEE Information Theory Workshop, 2024.

[91] Guangfeng Yan, Tan Li, Yuanzhang Xiao, Hanxu Hou, Congduan Li, and Linqi Song, "Truncated non-uniform quantization for distributed SGD," in IEEE Information Theory Workshop, 2024.

[90] Peikai Li, Jingjie Lv, Linqi Song, Li Zhang, and Hanxu Hou, "New Cauchy MDS array codes with flexible sub-packetization and efficient decoding," in IEEE Information Theory Workshop, 2024.

[89] Siyuan Wang, Jianping Wang, and Linqi Song, "Addressing fluctuating stragglers in distributed matrix multiplication via fountain codes," in IEEE Information Theory Workshop, 2024.

[88] Yuxuan Yao, Han Wu, Zhijiang Guo, Biyan Zhou, Jiahui Gao, Sichun Luo, Hanxu Hou, Xiaojin Fu, and Linqi Song, "Learning from correctness without prompting makes LLM efficient reasoner, " in Conference on Language Modeling (COLM), 2024.

[87] Haochen Tan, Zhijiang Guo, Zhan Shi, Lu Xu, Zhili Liu, Yunlong Feng, Xiaoguang Li, Yasheng Wang, Lifeng Shang, Qun Liu, and Linqi Song, “ProxyQA: an alternative framework for evaluating long-form text generation with large language models”, in Annual Meeting of the Association for Computational Linguistics (ACL), 2024.

[86] Yinya Huang, Ruixin Hong, Hongming Zhang, Wei Shao, Zhicheng YANG, Dong Yu, Changshui Zhang, Xiaodan Liang, and Linqi Song, “CLOMO: Counterfactual logical modification with large language models”, in Annual Meeting of the Association for Computational Linguistics (ACL), 2024.

[85] Tianqi Zhong, Zhaoyi Li, Quan Wang, Defu Lian, Ying Wei, Linqi Song, and Zhendong Mao, “Benchmarking and improving compositional generalization of multi-aspect controllable text generation”, in Annual Meeting of the Association for Computational Linguistics (ACL), 2024.

[84] Shuqi Liu , Bowei He, and Linqi Song, “Bi-chainer: automated large language models reasoning with bidirectional chaining”, in Annual Meeting of the Association for Computational Linguistics (ACL) (findings), 2024.

[83] Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song, Defu Lian, and Ying Wei, “Understanding and patching compositional reasoning in LLMs”, in Annual Meeting of the Association for Computational Linguistics (ACL) (findings), 2024.

[82] Xiaoming Xue, Liang Feng, Cuie Yang, Songbai Liu, Linqi Song, and Kay Chen Tan, "Multiobjective sequential transfer optimization: benchmark problems and preliminary results," in IEEE Congress on Evolutionary Computation (CEC), 2024.

[81] Xilei Wu, Peiqiu Huang, Linqi Song, Hailin Liu, and Qingfu Zhang, "Multiobjective bayesian optimization for antenna placement in in-building distributed antenna systems," in IEEE Congress on Evolutionary Computation (CEC), 2024.

[80] Zhengyi Jiang, Bin Yu, Zhongyi Huang, Linqi Song, Bo Bai, Gong Zhang, and Hanxu Hou, "Tight lower bound on cross-rack update bandwidth and explicit constructions,"  in IEEE International Symposium on Information Theory (ISIT), 2024.

[79] Wenhao Liu, Zhengyi Jiang, Zhongyi Huang, Linqi Song, and Hanxu Hou, "Reed-Solomon codes over cyclic polynomial ring with lower encoding/decoding complexity," in IEEE International Symposium on Information Theory (ISIT), 2024.

[78] Panyu Zhu, Jingjie Lv, Yunghsiang Sam Han, Linqi Song, and Hanxu Hou, "New EVENODD+ codes with more flexible parameters and lower complexity," in IEEE International Symposium on Information Theory (ISIT), 2024.

[77] Yao Hu, Rui Liu, Jiaqi Zhang, Zhian Huang, Linqi Song, and Kay Chen Tan, "Heterogeneous structured federated learning with graph convolutional aggregation for MRI-based mental disorder diagnosis," in International Joint Conference on Neural Network (IJCNN), 2024. 

[76] Yuxuan Yao, Sichun Luo, Haohan Zhao, Guanzhi Deng, and Linqi Song, "Can LLM substitute human labeling? A case study of fine-grained Chinese address entity recognition dataset for UAV delivery," in Resource at The ACM Web Conference, 2024.

[75] Haokun Lin, Haoli Bai, Zhili LIU, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, and Zhenan Sun, "MoPE-CLIP: Structured pruning for efficient vision-language models with module-wise pruning error metric," in Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

[74] Ke Wang, Houxing Ren, Aojun Zhou, Zimu Lu, Sichun Luo, Weikang Shi, Renrui Zhang, Linqi Song, Mingjie Zhan, and Hongsheng Li, "MathCoder: Seamless code integration in LLMs for enhanced mathematical reasoning," in International Conference on Learning Representations (ICLR), 2024.

[73] Aojun Zhou, Ke Wang, Zimu Lu, Weikang Shi, Sichun Luo, Zipeng Qin, Shaoqing Lu, Anya Jia, Linqi Song, Mingjie Zhan, and Hongsheng Li, "Solving challenging math word problems using GPT-4 code interpreter with code-based self-verification," in International Conference on Learning Representations (ICLR), 2024.

[72] Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, and Xiaodan Liang, "MUSTARD: Mastering uniform synthesis of theorem and proof data," in International Conference on Learning Representations (ICLR), 2024.

[71] Sichun Luo, Jiansheng Wang, Aojun Zhou, Li Ma, and Linqi Song, "Large language models augmented rating prediction in recommender system," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.

[70] Hanxu Hou and Linqi Song, "On the MDS condition of generalized expanded- Blaum-Roth codes," in 18th International Symposium on Problems of Redundancy in Information and Control Systems (REDUNDANCY), 2023.

[69] Hanxu Hou and Linqi Song, "Triple-fault-tolerant binary MDS array codes with lower encoding complexity," in 18th International Symposium on Problems of Redundancy in Information and Control Systems (REDUNDANCY), 2023.

[68] Yuxuan YAO, Han Wu, Qiling Xu, and Linqi Song, "Fine-grained conversational decoding," in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

[67] Haochen Tan, Han Wu, Wei Shao, Xinyun Zhang, Mingjie Zhan, Zhaohui Hou, Ding Liang, and Linqi Song, "Reconstruct before summarize: An efficient two-step framework for condensing and summarizing meeting transcripts," in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

[66] Siyuan Wang, Qifa Yan, Jingjing Zhang, Jianping Wang, and Linqi Song, "Matrix completion via coded distributed alternating least squares," in International Conference on Wireless Communications and Signal Processing (WCSP), 2023.

[65] Pingping Li, Leilei Yu, Linqi Song, and Hanxu Hou, "A fast algorithm for finding the roots of polynomials over finite fields," in International Conference on Wireless Communications and Signal Processing (WCSP), 2023.

[64] Bin Yu, Zhengyi Jiang, Zhongyi Huang, Linqi Song, and Hanxu Hou, "Product-matrix construction of minimum storage rack-aware regenerating codes," in International Conference on Wireless Communications and Signal Processing (WCSP), 2023.

[63] Yongkang Luo, Peiyi Han, Wenjian Luo, Shaocong Xue, Kesheng Chen, and Linqi Song, "A framework of large-scale peer-to-peer learning system", in 30th International Conference on Neural Information Processing (ICONIP), 2023. 

[62] Sichun Luo, Chen Ma, Yuanzhang Xiao, and Linqi Song, "Improving long-tail item recommendation performance with graph augmentation," in Conference on Information and Knowledge Management (CIKM), 2023.

[61] Mengzhe Ruan, Guangfeng Yan, Yuanzhang Xiao, Linqi Song, and Weitao Xu, "Adaptive top-k in SGD for communication-efficient distributed learning," in IEEE Global Communications Conference (GLOBECOM), 2023.

[60] Xi Zhang, Dan Song, Linqi Song, and Congduan Li, “Semantic communication based on entity information enhancement”, in IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2023.

[59] Han Wu, Mingjie Zhan, Haochen Tan, Zhaohui Hou, Ding Liang, and Linqi Song, “VCSUM: A Versatile Chinese Meeting Summarization Dataset”, in Annual Meeting of the Association for Computational Linguistics (ACL) (findings), 2023.

[58] Han Wu, Haochen Tan, Mingjie Zhan, Gangming Zhao, Shaoqing Lu, Ding Liang, and Linqi Song, "Learning Locality and Isotropy in Dialogue Modeling", in 11th International Conference on Learning Representations (ICLR), 2023.

[57] Tong Xu, Angela Lu, Abhay Mishra, Zengyan Liu, and Linqi Song, "Digital social movements and the performance of sharing economy participants: A study of black lives matter and Airbnb", in 32nd Workshop on Information Technologies and Systems (WITS 2022): Embracing Digital Asset Disruption in the Digital Economy, 2022.

[56] Shuqi Liu, Siuying Man, and Linqi Song, "An NLP-empowered virtual course assistant for online teaching and learning", in IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2022.

[55] Yujia Wang, Shuqi Liu, and Linqi Song, "Designing an educational chatbot with joint intent classification and slot filling", in IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2022.

[54] Haoyu Chen, Linqi Song, Zhenxing Qian, Xinpeng Zhang, and Kede Ma, "Hiding Images in Deep Probabilistic Models", in Conference on Neural Information Processing Systems (NeurIPS), 2022.

[53] Longteng Duan, Wei Shao and Linqi Song, "Facial expression recognition based on data augmentation and swin-transformer", in IEEE Region 10 Conference, 2022.

[52] Mingyang Liu, Yaxin Ke, Yichen Zhang, Wei Shao and Linqi Song, "Speech emotion recognition based on deep learning", in IEEE Region 10 Conference, 2022.

[51] Sichun Luo, Yuanzhang Xiao, Yang Liu, Congduan Li, and Linqi Song, "Towards communication efficient and fair federated personalized sequential recommendation", in 5th International Conference on Information Communication and Signal Processing (ICICSP), 2022.

[50] Sichun Luo, Xinyi Zhang, Yuanzhang Xiao, and Linqi Song, "HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations", in Conference on Information and Knowledge Management (CIKM), 2022.

[49] Zengyan Liu, Linqi Song, and Christina Fragouli, "Federated Multi-Armed Bandits With Vector Rewards for Aspect-Based Recommendations", in IEEE Global Communications Conference (GLOBECOM), 2022.

[48] Sichun Luo, Yuanzhang Xiao, and Linqi Song, "Personalized Federated Recommendation via Joint Representation Learning, User Clustering, and Model Adaptation", in Conference on Information and Knowledge Management (CIKM), 2022.

[47] Yao Hu, Zhi-An Huang, Rui Liu, Xiaoming Xue, Linqi Song, and Kay Chen Tan, "A dual-stage pseudo-labeling method for the diagnosis of mental disorder on MRI scans", in International Joint Conference on Neural Network (IJCNN), 2022.

[46] Wei Shao, Lei Huang, Shuqi Liu, Shihua Ma, and Linqi Song, "Towards better understanding with uniformity and explicit regularization of embeddings in embedding-based neural topic models", in International Joint Conference on Neural Network (IJCNN), 2022.

[45] Han Wu, Haochen Tan, Kun Xu, Shuqi Liu, Lianwei Wu, and Linqi Song, "Zero-shot cross-lingual conversational semantic role labeling", in North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT) (findings), 2022.

[44] Jian Xu, Shao-Lun Huang, Linqi Song, and Tian Lan, "Byzantine-robust federated learning through collaborative malicious gradient filtering", in IEEE International Conference on Distributed Computing Systems (ICDCS), 2022.

[43] Huanqi Yang, Hongbo Liu, Yuezhong Wu, Chengwen Luo, Wei Li, Albert Zomaya, Linqi Song and Weitao Xu, "Vehicle-key: A secret key establishment scheme for LoRa-enabled IoV communications", in IEEE International Conference on Distributed Computing Systems (ICDCS), 2022.

[42] Haochen Tan, Wei Shao, Han Wu, Ke Yang, and Linqi Song, "A sentence is worth 128 pseudo tokens: a semantic-aware contrastive learning framework for sentence embeddings", in Annual Meeting of the Association for Computational Linguistics (ACL) (findings), 2022.

[41] Tan Li and Linqi Song, "Federated adaptive bandits aided caching for heterogeneous edge servers with uncertainty," in IEEE Wireless Communications and Networking Conference (WCNC), 2022.

[40] Xinlin Li, Shuqi Liu, Xinyi Zhang, and Linqi Song, "Predicting downside in stock market using knowledge and news data", in International Conference on Parallel and Distributed Systems (ICPADS), 2021.

[39] Han Wu, Kun Xu, and Linqi Song, "CSAGN: Conversational structure aware graph network for conversational semantic role labeling", in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021.

[38] Tong Xu, Angela Lu, Abhay Mishra, Linqi Song, Zengyan Liu, "Racial bias during “Black Lives Matter”: How social movement reshapes Airbnb host performance", in International Conference on Information Systems (ICIS), 2021.

[37] Guangfeng Yan, Shaolun Huang, Tian Lan, and Linqi Song, "DQ-SGD: Dynamic quantization in SGD for communication-efficient distributed learning," in IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS), 2021.

[36] Han Wu, Kun Xu, Linfeng Song, Lifeng Jin, Haisong Zhang, and Linqi Song, "Domain-adaptive pretraining methods for dialogue understanding," in The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP), 2021.

[35] Siyuan Wang, Qifa Yan, Jingjing Zhang, Jianping Wang, and Linqi Song, "Coded alternating least squares for straggler mitigation in distributed recommendations," in IEEE International Symposium on Information Theory (ISIT), 2021.

[34] Boyu He, Han Wu, Congduan Li, Linqi Song, and Weigang Chen, "K-CSRL: Knowledge enhanced conversational semantic role labeling," in 13th International Conference on Machine Learning and Computing (ICMLC), 2021.

[33] Rasmus Vestergaard, Osama Hanna, Linqi Song, Daniel E. Lucani, Christina Fragouli, "On coded broadcasting for wireless recommendation systems," in IEEE International Conference on Communications (ICC), 2021.

[32] Jian Xu, Shaolun Huang, Linqi Song, and Tian Lan, "Live gradient compensation for evading stragglers in distributed learning," in IEEE International Conference on Computer Communications (INFOCOM), 2021.

[31] Kun Xu, Haochen Tan, Linfeng Song, Han Wu, Haisong Zhang, Linqi Song, and Dong Yu, "Semantic role labeling guided multi-turn dialogue rewriter," in 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020.

[30] W. Chen, W. Chen, L. Song, "Enhancing deep multimedia recommendations using graph embeddings," in IEEE 3rd International Conference on Multimedia Information Processing and Retrieval (MIPR), 2020. (Conf. acceptance rate 19.5%) (Best Paper Award)

[29] C. Li, J. He, S. Liu, D. Guo, and L. Song, "On secrecy key of a class of secure asymmetric multilevel diversity coding system," in IEEE International Symposium on Information Theory (ISIT), 2020.

[28] T. Li, L. Song, and C. Fragouli, "Federated recommendation system via differential privacy," in IEEE International Symposium on Information Theory (ISIT), 2020.

[27] J. He, C. Li, and L. Song, "Coded caching with heterogeneous user groups," in IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2020.

[26] H. Tang, J. Wang, L. Song, J. Song, "Scheduling to minimize age of information in multi-state time-varying networks with power constraints," in IEEE 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2019.

[25] Y. Bai, L. Chen, L. Song, J. Xu, "Bayesian Stackelberg Game for Risk-aware Edge Computation Offloading," in 6th ACM Workshop on Moving Target Defense (MTD'19), 2019.

[24] T. Li, Y. Xiao, L. Song, "Deep reinforcement learning based residential demand side management with edge computing," in IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2019.

[23] C. Shi, L. Chen, C. Shen, L. Song, J. Xu, "Privacy-aware edge computing based on adaptive DNN partitioning," in IEEE Global Communications Conference (GLOBECOM), 2019.

[22] L. Zhang, L. Song, J. Xu, "Preventing malware propagation in D2D offloading networks with strategic mobile users," in IEEE Global Communications Conference (GLOBECOM), 2019.

[21] M. Yang, L. Song, J. Xu, C. Li, and G. Tan, "The tradeoff between privacy and accuracy in anomaly detection using federated XGBoost," in IJCAI Workshop: 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML 2019), arXiv:1907.07157, 2019.

[20] L. Song, C. Fragouli, and D. Shah, "Interactions between learning and broadcasting in wireless recommendation systems," in IEEE International Symposium on Information Theory (ISIT), 2019.

[19] D. Data, L. Song, and S. Diggavi, "Data encoding methods for byzantine-resilient distributed optimization," in IEEE International Symposium on Information Theory (ISIT), 2019.

[18] L. Song, J. Xu, and C. Li, "Active Learning for Streaming Data in A Contextual Bandit Framework," in ACM 5th International Conference on Computing and Data Engineering, pp. 29-35, 2019. (Best Presentation Award)

[17] L. Song, “A binary randomized coding scheme for pliable index coding with multiple requests,” in International Symposium on Turbo Codes and Iterative Information Processing (ISTC), 2018.

[16] L. Song, and J. Xu, “Dynamic edge caching with popularity drifting,” in IEEE Information Theory Workshop (ITW), 2018.

[15] L. Song, C. Fragouli, and D. Shah, “Recommender systems over wireless: challenges and opportunities,” in IEEE Information Theory Workshop (ITW), 2018.

[14] D. Data, L. Song, and S. Diggavi, “Data encoding for byzantine-resilient distributed gradient descent." In IEEE 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 863-870, 2018.

[13] S. Rajan, L. Song, and C. Fragouli, “Distributed computing trade-offs with random connectivity,” in IEEE International Symposium on Information Theory (ISIT), 2018.

[12] M. Karmoose, L. Song, M. Cardone, and C. Fragouli, “Privacy in index coding: improved bounds and coding schemes,” in IEEE International Symposium on Information Theory (ISIT), 2018.

[11] L. Song, S. Rajan, and C. Fragouli, “The benefit of being flexible in distributed computation,” in IEEE Information Theory Workshop (ITW), 2017.

[10] M. Karmoose, L. Song, M. Cardone, and C. Fragouli, “Preserving privacy while broadcasting: k - limited-access schemes,” in IEEE Information Theory Workshop (ITW), 2017.

[9] L. Song, and C. Fragouli, “Making recommendations bandwidth aware,” IEEE International Symposium on Information Theory (ISIT), 2243-2247, Aachen, Germany, 2017.

[8] L. Song, and C. Fragouli, “A pliable index coding approach to data shuffling,” IEEE International Symposium on Information Theory (ISIT), 2558-2562, Aachen, Germany, 2017.

[7] M. Karmoose, L. Song, M. Cardone, and C. Fragouli, “Private broadcasting: an index coding approach,” IEEE International Symposium on Information Theory (ISIT), 2543-2547, Aachen, Germany, 2017.

[6] L. Song, and C. Fragouli, “A polynomial-time algorithm for pliable index coding,” IEEE International Symposium on Information Theory (ISIT), 120-124, Barcelona, Spain, 2016.

[5] L. Song, and C. Fragouli, “Content-type coding”, in Network Coding (NetCod), IEEE International Symposium on, Sydney, Australia, 2015.

[4] L. Song, Y. Xiao, and M. van der Schaar, “Non-stationary demand side management method for smart grids,” IEEE ICASSP 2014.

[3] L. Song, C. Tekin, and M. van der Schaar, “Clustering based online learning in recommender systems: a bandit approach,” IEEE ICASSP 2014.

[2] J. Xu, J. Y. Xu, L. Song, G. Pottie, and M. van der Schaar, “Context-driven online learning for activity classification in wireless health,” Global Communications Conference (GLOBECOM), 2014 IEEE, pp. 2423-2428, 2014.

[1] L. Song, J. Wang, C. Pan, and J. Fu, “A normalized LLR soft information demapping method in DTMB system,” IEEE ICCS, 2008.