1 citations · 1 across the 13 of their papers we have counts for
14 papers
Aligning Shared and Routed Experts for Cross-Subject EEG Generalization
Zhi Zhang, Yan Liu, Zhejing Hu +7
Cross-subject EEG generalization is challenging due to substantial heterogeneity across subjects. Existing methods typically learn either a shared subject-invariant model or multip…
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…
Evolving and Executing Research Plans via Double-Loop Multi-Agent Collaboration
Zhi Zhang, Yan Liu, Zhejing Hu +3
Automating the end-to-end scientific research process poses a fundamental challenge: it requires both evolving high-level plans that are novel and sound, and executing these plans…
Who Decides How Knowing Becomes Doing? Redistributing Authority in Human-AI Music Co-Creation
Zhejing Hu, Yan Liu, Zhi Zhang +3
In the era of human-AI co-creation, the maxim "knowing is easy, doing is hard" is redefined. AI has the potential to ease execution, yet the essence of "hard" lies in who governs t…
MusicScaffold: Bridging Machine Efficiency and Human Growth in Adolescent Creative Education through Generative AI
Zhejing Hu, Yan Liu, Zhi Zhang +4
Adolescence is marked by strong creative impulses but limited strategies for structured expression, often leading to frustration or disengagement. While generative AI lowers techni…
Predicting Multi-Type Talented Students in Secondary School Using Semi-Supervised Machine Learning
Xinzhe Zheng, Zhen-Qun Yang, Jiannong Cao +1
Talent identification plays a critical role in promoting student development. However, traditional approaches often rely on manual processes or focus narrowly on academic achieveme…
Structure-Guided Memory Consolidation for Mitigating Compounding Errors in Literature Review Generation
Zhi Zhang, Yan Liu, Zhejing Hu +4
Compounding errors pose a significant challenge in automatic literature review generation, as inaccuracies can cascade across multi-stage retrieval and generation workflows. Existi…
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…
Data-Efficient Model for Psychological Resilience Prediction based on Neurological Data
Zhi Zhang, Yan Liu, Mengxia Gao +7
Psychological resilience, defined as the ability to rebound from adversity, is crucial for mental health. Compared with traditional resilience assessments through self-reported que…
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…
FairTP: A Prolonged Fairness Framework for Traffic Prediction
Jiangnan Xia, Yu Yang, Jiaxing Shen +2
Traffic prediction plays a crucial role in intelligent transportation systems. Existing approaches primarily focus on improving overall accuracy, often neglecting a critical issue:…
DMP_AI: An AI-Aided K-12 System for Teaching and Learning in Diverse Schools
Zhen-Qun Yang, Jiannong Cao, Xiaoyin Li +4
The use of Artificial Intelligence (AI) has gained momentum in education. However, the use of AI in K-12 education is still in its nascent stages, and further research and developm…
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…