1 citations · 1 across the 7 of their papers we have counts for
7 papers
Beyond Success and Failure: Length-Aware Contrastive Learning for GUI Agents
Chengyang Gu, Le Zhang, Jingbo Zhou +6
Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) have shown strong potential for automating tasks across diverse digital environments, wher…
LLM-Based Hierarchical Coordinated Control with Continuation-Aware Policy Learning
Changhong He, Jinda Gao, Xinkuan Liu +3
Coordinating multiple interacting units in complex engineering systems is challenging when system interactions are difficult to model, operational information is heterogeneous, and…
CHAT: Beyond Contrastive Graph Transformer for Link Prediction in Heterogeneous Networks
Shengming Zhang, Le Zhang, Jingbo Zhou +1
Link prediction in heterogeneous networks is crucial for understanding the intricacies of network structures and forecasting their future developments. Traditional methodologies of…
Labor Migration Modeling through Large-scale Job Query Data
Zhuoning Guo, Le Zhang, Hengshu Zhu +3
Accurate and timely modeling of labor migration is crucial for various urban governance and commercial tasks, such as local policy-making and business site selection. However, exis…
Convergence-aware Clustered Federated Graph Learning Framework for Collaborative Inter-company Labor Market Forecasting
Zhuoning Guo, Hao Liu, Le Zhang +3
Labor market forecasting on talent demand and supply is essential for business management and economic development. With accurate and timely forecasts, employers can adapt their re…
DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives
Leilei Ding, Dazhong Shen, Chao Wang +3
Graph Convolutional Networks (GCNs) have become pivotal in recommendation systems for learning user and item embeddings by leveraging the user-item interaction graph's node informa…
ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness
Yunfei Zhang, Chuan Qin, Dazhong Shen +4
During the past few decades, cognitive diagnostics modeling has attracted increasing attention in computational education communities, which is capable of quantifying the learning…