3 citations · 3 across the 5 of their papers we have counts for
5 papers
CT: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic--Vehicle Coordination
Yuyang Chen, Kaiyan Zhao, Yiming Wang +3
State-of-the-art (SOTA) urban traffic control increasingly employs Multi-Agent Reinforcement Learning (MARL) to coordinate Traffic Light Controllers (TLCs) and Connected Autonomous…
Bridging Molecular Graphs and Large Language Models
Runze Wang, Mingqi Yang, Yanming Shen
While Large Language Models (LLMs) have shown exceptional generalization capabilities, their ability to process graph data, such as molecular structures, remains limited. To bridge…
LemmaHead: RAG Assisted Proof Generation Using Large Language Models
Tianbo Yang, Mingqi Yan, Hongyi Zhao +1
Developing the logic necessary to solve mathematical problems or write mathematical proofs is one of the more difficult objectives for large language models (LLMS). Currently, the…
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track
Chengxuan Ying, Mingqi Yang, Shuxin Zheng +7
In this technical report, we present our solution of KDD Cup 2021 OGB Large-Scale Challenge - PCQM4M-LSC Track. We adopt Graphormer and ExpC as our basic models. We train each mode…
Breaking the Expressive Bottlenecks of Graph Neural Networks
Mingqi Yang, Yanming Shen, Heng Qi +1
Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressiveness of graph neural networks (GNNs), showing that the neighborhood aggregation GNNs w…