Publications

2025

1. IEEE ASRU

   

   LauraTSE: Target Speaker Extraction using Auto-Regressive Decoder-Only Language Models

   Beilong Tang, Bang Zeng, and Ming Li

   IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2025

   arXiv Bib Code

   @article{tang2025lauratse,
     title = {LauraTSE: Target Speaker Extraction using Auto-Regressive Decoder-Only Language Models},
     author = {Tang, Beilong and Zeng, Bang and Li, Ming},
     journal = {IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)},
     year = {2025},
   }

2. IEEE ASRU

   

   SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization

   Beilong Tang, Xiaoxiao Miao, Xin Wang, and 1 more author

   IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2025

   arXiv Bib Code

   @article{tang2025sef,
     title = {SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization},
     author = {Tang, Beilong and Miao, Xiaoxiao and Wang, Xin and Li, Ming},
     journal = {IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)},
     year = {2025},
   }

3. Preprint

   

   Diarization-Aware Multi-Speaker Automatic Speech Recognition via Large Language Models

   Yuke Lin, Ming Cheng, Ze Li, and 2 more authors

   arXiv preprint arXiv:2506.05796, 2025

   arXiv

2024

1. Preprint

   

   TSELM: Target Speaker Extraction using Discrete Tokens and Language Models

   Beilong Tang, Bang Zeng, and Ming Li

   arXiv preprint arXiv:2409.07841, 2024

   arXiv Bib Code

   @article{tang2024tselm,
     title = {TSELM: Target Speaker Extraction using Discrete Tokens and Language Models},
     author = {Tang, Beilong and Zeng, Bang and Li, Ming},
     journal = {arXiv preprint arXiv:2409.07841},
     year = {2024},
   }

2. INFOCOM Demo

   

   Fedkit: Enabling Cross-Platform Federated Learning for Android and iOS

   Sichang He, Beilong Tang, Boyan Zhang, and 4 more authors

   In IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2024

   arXiv Bib Code

   @inproceedings{FedKit,
     author = {He, Sichang and Tang, Beilong and Zhang, Boyan and Shao, Jiaoqi and Ouyang, Xiaomin and Nugraha, Daniel Nata and Luo, Bing},
     booktitle = {IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},
     title = {Fedkit: Enabling Cross-Platform Federated Learning for Android and iOS},
     year = {2024},
     volume = {},
     number = {},
     pages = {1-2},
     keywords = {Training;Data analysis;Federated learning;Conferences;Computational modeling;Pipelines;Production},
     doi = {10.1109/INFOCOMWKSHPS61880.2024.10620662},
   }

3. MobiHoc Demo

   

   FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics

   Jiaxiang Geng, Beilong Tang, Boyan Zhang, and 2 more authors

   ACM MobiHoc, 2024

   arXiv Bib

   @article{geng2024fedcampus,
     title = {FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning \& Analytics},
     author = {Geng, Jiaxiang and Tang, Beilong and Zhang, Boyan and Shao, Jiaqi and Luo, Bing},
     journal = {ACM MobiHoc},
     year = {2024},
   }