activity
20192023
most citedMulti-Agent Game Abstraction via Graph Attention Neural Network

20 citations · 50 across the 9 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

cs.IR2023★ 1 cited

Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems

Hengchang Hu, Wei Guo, Yong Liu +1

In sequential recommendation, multi-modal information (e.g., text or image) can provide a more comprehensive view of an item's profile. The optimal stage (early or late) to fuse mo…

cs.LG2023★ 14 cited

Can Large Language Models Empower Molecular Property Prediction?

Chen Qian, Huayi Tang, Zhirui Yang +2

Molecular property prediction has gained significant attention due to its transformative potential in multiple scientific disciplines. Conventionally, a molecule graph can be repre…

cs.MA2023

Multi-Agent Cooperation via Unsupervised Learning of Joint Intentions

Shanqi Liu, Weiwei Liu, Wenzhou Chen +2

The field of cooperative multi-agent reinforcement learning (MARL) has seen widespread use in addressing complex coordination tasks. While value decomposition methods in MARL have…

cs.LG2023

Data-Free Quantization via Mixed-Precision Compensation without Fine-Tuning

Jun Chen, Shipeng Bai, Tianxin Huang +3

Neural network quantization is a very promising solution in the field of model compression, but its resulting accuracy highly depends on a training/fine-tuning process and requires…

cs.LG2023★ 2 cited

Towards Understanding the Generalization of Graph Neural Networks

Huayi Tang, Yong Liu

Graph neural networks (GNNs) are the most widely adopted model in graph-structured data oriented learning and representation. Despite their extraordinary success in real-world appl…

cs.RO2023★ 4 cited

Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning

Shanqi Liu, Yujing Hu, Runze Wu +5

Real-world cooperation often requires intensive coordination among agents simultaneously. This task has been extensively studied within the framework of cooperative multi-agent rei…