Kaili Ma

21 papers A* 6A 1Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2025 — conf
Retrieval-Augmented Generation with Hierarchical Knowledge.
EMNLP (Findings)
Haoyu Huang, Yongfeng Huang, Junjie Yang, Zhenyu Pan, Yongqiang Chen, Kaili Ma, Hongzhi Chen, James Cheng
2025 J jnl
Retrieval-Augmented Generation with Hierarchical Knowledge.
CoRR
Haoyu Huang, Yongfeng Huang, Junjie Yang, Zhenyu Pan, Yongqiang Chen, Kaili Ma, Hongzhi Chen, James Cheng
2024 J jnl
Solving the non-submodular network collapse problems via Decision Transformer.
Neural Networks
Kaili Ma, Han Yang, Shanchao Yang, Kangfei Zhao, Lanqing Li, Yongqiang Chen, Junzhou Huang, James Cheng, Yu Rong
2023 J jnl
Calibrating and Improving Graph Contrastive Learning.
Trans. Mach. Learn. Res.
Kaili Ma, Garry Yang, Han Yang, Yongqiang Chen, James Cheng
2023 J jnl
GRACE: A General Graph Convolution Framework for Attributed Graph Clustering.
ACM Trans. Knowl. Discov. Data
Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han
2023 J jnl
Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring.
Trans. Mach. Learn. Res.
Shanchao Yang, Kaili Ma, Baoxiang Wang, Tianshu Yu, Hongyuan Zha
2023 A* conf
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.
ICLR
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
2022 A* conf
Exact Shape Correspondence via 2D graph convolution.
NeurIPS
Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng
2022 J jnl
Invariance Principle Meets Out-of-Distribution Generalization on Graphs.
CoRR
Yongqiang Chen, Yonggang Zhang, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
2022 A* conf
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.
NeurIPS
Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng
2022 J jnl
Measuring and Improving the Use of Graph Information in Graph Neural Networks.
CoRR
Yifan Hou, Jie Zhang, James Cheng, Kaili Ma, Richard T. B. Ma, Hongzhi Chen, Ming-Chang Yang
2022 J jnl
Pareto Invariant Risk Minimization.
CoRR
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
2022 A* conf
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability.
ICLR
Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
2022 J jnl
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability.
CoRR
Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng
2021 J jnl
Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient.
CoRR
Shanchao Yang, Kaili Ma, Baoxiang Wang, Hongyuan Zha
2021 A conf
HyperGraph Convolution Based Attributed HyperGraph Clustering.
CIKM
Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, Bo Han
2021 J jnl
Improving Graph Representation Learning by Contrastive Regularization.
CoRR
Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng
2021 A* conf
Rethinking Graph Regularization for Graph Neural Networks.
AAAI
Han Yang, Kaili Ma, James Cheng
2020 A* conf
Measuring and Improving the Use of Graph Information in Graph Neural Networks.
ICLR
Yifan Hou, Jie Zhang, James Cheng, Kaili Ma, Richard T. B. Ma, Hongzhi Chen, Ming-Chang Yang
2020 J jnl
Rethinking Graph Regularization For Graph Neural Networks.
CoRR
Han Yang, Kaili Ma, James Cheng
2020 J jnl
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives.
CoRR
Guoji Fu, Yifan Hou, Jie Zhang, Kaili Ma, Barakeel Fanseu Kamhoua, James Cheng