6 citations · 11 across the 10 of their papers we have counts for
10 papers
FedRD: Reducing Divergences for Generalized Federated Learning via Heterogeneity-aware Parameter Guidance
Kaile Wang, Jiannong Cao, Yu Yang +2
Heterogeneous federated learning (HFL) aims to ensure effective and privacy-preserving collaboration among different entities. As newly joined clients require significant adjustmen…
FedCCA: Client-Centric Adaptation against Data Heterogeneity in Federated Learning on IoT Devices
Kaile Wang, Jiannong Cao, Yu Yang +2
With the rapid development of the Internet of Things (IoT), AI model training on private data such as human sensing data is highly desired. Federated learning (FL) has emerged as a…
Continuous Vision-Language-Action Co-Learning with Semantic-Physical Alignment for Behavioral Cloning
Xiuxiu Qi, Yu Yang, Jiannong Cao +4
Language-conditioned manipulation facilitates human-robot interaction via behavioral cloning (BC), which learns control policies from human demonstrations and serves as a cornersto…
Predicting Student Dropout Risk With A Dual-Modal Abrupt Behavioral Changes Approach
Jiabei Cheng, Zhen-Qun Yang, Jiannong Cao +2
Timely prediction of students at high risk of dropout is critical for early intervention and improving educational outcomes. However, in offline educational settings, poor data qua…
Modeling Behavior Change for Multi-model At-Risk Students Early Prediction (extended version)
Jiabei Cheng, Zhen-Qun Yang, Jiannong Cao +3
In the educational domain, identifying students at risk of dropping out is essential for allowing educators to intervene effectively, improving both academic outcomes and overall s…
Collaborative Imputation of Urban Time Series through Cross-city Meta-learning
Tong Nie, Wei Ma, Jian Sun +2
Urban time series, such as mobility flows, energy consumption, and pollution records, encapsulate complex urban dynamics and structures. However, data collection in each city is im…
Mixture of Knowledge Minigraph Agents for Literature Review Generation
Zhi Zhang, Yan Liu, Sheng-hua Zhong +3
Literature reviews play a crucial role in scientific research for understanding the current state of research, identifying gaps, and guiding future studies on specific topics. Howe…
Self-assessment, Exhibition, and Recognition: a Review of Personality in Large Language Models
Zhiyuan Wen, Yu Yang, Jiannong Cao +3
As large language models (LLMs) appear to behave increasingly human-like in text-based interactions, more and more researchers become interested in investigating personality in LLM…
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in Conversation
Zhiyuan Wen, Jiannong Cao, Yu Yang +2
Personality Recognition in Conversation (PRC) aims to identify the personality traits of speakers through textual dialogue content. It is essential for providing personalized servi…
Heterogeneity-aware Cross-school Electives Recommendation: a Hybrid Federated Approach
Chengyi Ju, Jiannong Cao, Yu Yang +2
In the era of modern education, addressing cross-school learner diversity is crucial, especially in personalized recommender systems for elective course selection. However, privacy…