469 citations · 1.3k across the 28 of their papers we have counts for
13 papers · 1 filter
Fewer Qubits, Better Choices: Coupling-Aware Sub-QUBO Selection for Quantum-Assisted Traffic Zone Partitioning
Qianwen Guo, Ruimin Ke
Near-term quantum optimizers accommodate roughly a hundred binary variables, requiring large Quadratic Unconstrained Binary Optimization problems to be decomposed into hardware-siz…
SimTIO: A Simulation-Grounded Multi-Agent LLM Framework for Compositional Traffic Intervention Optimization
Shuyang Li, Ruimin Ke
Traffic analysts must translate diagnosed bottlenecks into executable interventions without allowing local improvements to degrade network-wide performance. This study presents Sim…
GHR-VLM: Making Zero-Shot Transit Video Analytics Realizable with Grounded Hybrid Reasoning
Kaicong Huang, Weiheng Oh, Jack M. Reilly +2
Transit video understanding can provide valuable fine-grained data that conventional passenger counters and fare systems cannot capture. However, supervised video models require ta…
Risk-Adaptive Edge--Cloud Visual Reasoning for Communication-Efficient Autonomous Driving
Meng Ma, Shuyang Li, Naigang Wang +1
Cloud-hosted vision-language models (VLMs) offer greater contextual reasoning capabilities than smaller onboard models, but frequent visual uploads increase communication overhead…
Cooperative Platoon Routing and Dispatching via Edge-Assisted Hybrid Quantum Optimization
Talha Azfar, Ruimin Ke
Cooperative platooning can reduce the energy use of Connected and Autonomous Vehicle (CAV) fleets, but the routing problem becomes difficult when vehicles must meet on the same roa…
FedQML-Edge: Compact Quantum Feature Sketches for Communication-Constrained Roadside Federated Learning
Talha Azfar, Ruimin Ke
Roadside units (RSUs) supporting connected and autonomous vehicle corridors need compact models to decide when cooperative maneuvers should be rewarded, deferred, or disabled. Raw…
CARLA-GS: Decoupling Representation, Reasoning, and Physics Simulation for Autonomous Driving Corner-Case Synthesis
Kaicong Huang, Meng Ma, Ruimin Ke
Safety evaluation for autonomous driving is dominated by rare, safety-critical interactions, motivating simulators that can deliberately synthesize corner cases with photorealistic…
Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO
Shuyang Li, Ruimin Ke
The integration of Large Language Models (LLMs) with microscopic traffic simulation offers a promising path toward autonomous urban planning and intelligent transportation analysis…
Impact-Driven Quantum Decomposition for Traffic Zone Partitioning: A Hybrid Gate-Model Framework
Ruimin Ke, Talha Azfar, Kaicong Huang +1
Partitioning transportation networks into balanced and spatially coherent traffic zones is a fundamental yet computationally challenging task in intelligent transportation systems.…
Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes
Kaicong Huang, Talha Azfar, Weisong Shi +1
Reliable autonomous driving relies on large-scale, well-labeled data and robust models. However, manual data collection is resource-intensive, and traditional simulation suffers fr…
iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning
Kaicong Huang, Weiheng Oh, Thomas Guggisberg +1
Automated transit payment analysis is vital for scalable fare auditing and passenger analytics, yet practice still relies on limited manual inspection. Prior vision- and skeleton-b…
Hardware-Efficient Quantum Optimization for Transportation Networks via Compressed Adiabatic Evolution
Talha Azfar, Ruimin Ke, Sean He +2
Transportation systems such as urban logistics, vehicle routing, and infrastructure planning require solving large-scale combinatorial optimization problems under complex constrain…
Locatability-Guided Adaptive Reasoning for Image Geo-Localization with Vision-Language Models
Bo Yu, Fengze Yang, Yiming Liu +6
The emergence of Vision-Language Models (VLMs) has introduced new paradigms for global image geo-localization through retrieval-augmented generation (RAG) and reasoning-driven infe…