22 citations · 42 across the 7 of their papers we have counts for
7 papers
Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment
Yijie Deng, He Zhu, Wen Wang +3
Problem, Research Strategy, and Findings: The rise of large language models (LLMs) raises a key question for urban planning: which forms of professional planning knowledge can AI r…
PlanBench-V: A Spatial Planning Map Benchmark for Vision-Language Models
Minxin Chen, He Zhu, Junyou Su +3
Spatial planning maps are central to territorial governance, translating planning objectives, regulations, and spatial strategies into visual forms for decision-making, public comm…
Empirical Comparison of Forgetting Mechanisms for UCB-based Algorithms on a Data-Driven Simulation Platform
Minxin Chen
Many real-world bandit problems involve non-stationary reward distributions, where the optimal decision may shift due to evolving environments. However, the performance of some typ…
MambaRefine-YOLO: A Dual-Modality Small Object Detector for UAV Imagery
Shuyu Cao, Minxin Chen, Yucheng Song +2
Small object detection in Unmanned Aerial Vehicle (UAV) imagery is a persistent challenge, hindered by low resolution and background clutter. While fusing RGB and infrared (IR) dat…
PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models
He Zhu, Junyou Su, Minxin Chen +4
In the field of urban planning, existing Vision-Language Models (VLMs) frequently fail to effectively analyze and evaluate planning maps, despite the critical importance of these v…
Solving multiscale elliptic problems by sparse radial basis function neural networks
Zhiwen Wang, Minxin Chen, Jingrun Chen
Machine learning has been successfully applied to various fields of scientific computing in recent years. In this work, we propose a sparse radial basis function neural network met…
MIM: A deep mixed residual method for solving high-order partial differential equations
Liyao Lyu, Zhen Zhang, Minxin Chen +1
In recent years, a significant amount of attention has been paid to solve partial differential equations (PDEs) by deep learning. For example, deep Galerkin method (DGM) uses the P…