I am pleased to announce that our latest paper, "LLM4GKID: Identifying Ghost Kitchens through Large Language Models and Multi-source Data Integration," has been accepted for publication in IEEE Transactions on Computational Social Systems (TCSS).

This work marks a significant milestone for the RGC-funded project, "Bridging Bites and Bytes: Measuring, Modelling, and Planning for the Emerging Online-offline Nexus in Urban Food Environments" (PI: Prof. Yang). The proposed LLM4GKID framework leverages the semantic power of Large Language Models to align disparate data sources, providing a scalable solution for detecting "ghost kitchens" within complex urban foodscapes.

This achievement is the result of a dedicated collaborative effort. I would like to extend my sincere thanks to my teammates, Yihong and Chaofan, for their hard work, and to Prof. Yang for his invaluable supervision and guidance throughout the process.

I also wish to express my gratitude to the anonymous reviewers and the editor, Prof. Bin Hu, for their constructive feedback and efforts in improving the quality of this manuscript.