A sparse integrative cluster analysis for understanding soybean phenotypes. - Jinbo Bi; Jiangwen Sun; Tingyang Xu; Jin Lu 001; Yansong Ma; Lijuan Qiu (BIBM, 2014)

Translating Effective Paper-Based Disease Management into Electronic Medical Systems. - Tingyang Xu; Jinbo Bi; Michelle M. Cloutier (ICHI, 2014)

Quantifying feed efficiency of dairy cattle for genome-wide association analysis. - Tingyang Xu; Jiangwen Sun; Erin E. Connor; Jinbo Bi (BIBM, 2015)

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization. - Jiangwen Sun; Jin Lu 001; Tingyang Xu; Jinbo Bi (ICML, 2015)

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction. - Tingyang Xu; Jiangwen Sun; Jinbo Bi (KDD, 2015)

Identifying and quantifying nonlinear structured relationships in complex manufactural systems. - Tingyang Xu; Tan Yan; Dongjin Song; Wei Cheng 002; Haifeng Chen; Geoff Jiang; Jinbo Bi (IEEE BigData, 2017)

Latent Sparse Modeling of Longitudinal Multi-Dimensional Data. - Ko-Shin Chen; Tingyang Xu; Jinbo Bi (AAAI, 2018)

Progressive Feature Alignment for Unsupervised Domain Adaptation. - Chaoqi Chen; Weiping Xie; Wenbing Huang 001; Yu Rong 001; Xinghao Ding; Yue Huang 001; Tingyang Xu; Junzhou Huang (CVPR, 2019)

DTWNet: a Dynamic Time Warping Network. - Xingyu Cai; Tingyang Xu; Jinfeng Yi; Junzhou Huang; Sanguthevar Rajasekaran (NeurIPS, 2019)

Unsupervised Adversarial Graph Alignment with Graph Embedding. - Chaoqi Chen; Weiping Xie; Tingyang Xu; Yu Rong 001; Wen-bing Huang 001; Xinghao Ding; Yue Huang 001; Junzhou Huang (CoRR, 2019)

The Truly Deep Graph Convolutional Networks for Node Classification. - Yu Rong 001; Wenbing Huang 001; Tingyang Xu; Junzhou Huang (CoRR, 2019)

The General Black-box Attack Method for Graph Neural Networks. - Heng Chang; Yu Rong 001; Tingyang Xu; Wenbing Huang 001; Honglei Zhang; Peng Cui 001; Wenwu Zhu 001; Junzhou Huang (CoRR, 2019)

Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks. - Tian Bian; Xi Xiao; Tingyang Xu; Peilin Zhao; Wenbing Huang 001; Yu Rong 001; Junzhou Huang (AAAI, 2020)

A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models. - Heng Chang; Yu Rong 001; Tingyang Xu; Wenbing Huang 001; Honglei Zhang; Peng Cui 001; Wenwu Zhu 001; Junzhou Huang (AAAI, 2020)

Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation. - Chaochao Yan; Sheng Wang 001; Jinyu Yang; Tingyang Xu; Junzhou Huang (BCB, 2020)

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification. - Yu Rong 001; Wenbing Huang 001; Tingyang Xu; Junzhou Huang (ICLR, 2020)

Deep Graph Learning: Foundations, Advances and Applications. - Yu Rong 001; Tingyang Xu; Junzhou Huang; Wenbing Huang 001; Hong Cheng 001; Yao Ma 001; Yiqi Wang 001; Tyler Derr; Lingfei Wu 001; Tengfei Ma 001 (KDD, 2020)

Self-Supervised Graph Transformer on Large-Scale Molecular Data. - Yu Rong 001; Yatao Bian; Tingyang Xu; Weiyang Xie; Ying Wei 001; Wenbing Huang 001; Junzhou Huang (NeurIPS, 2020)

Deep Multimodal Fusion by Channel Exchanging. - Yikai Wang 001; Wenbing Huang 001; Fuchun Sun 001; Tingyang Xu; Yu Rong 001; Junzhou Huang (NeurIPS, 2020)

Graph Representation Learning via Graphical Mutual Information Maximization. - Zhen Peng 005; Wenbing Huang 001; Minnan Luo; Qinghua Zheng; Yu Rong 001; Tingyang Xu; Junzhou Huang (WWW, 2020)

Spectral Graph Attention Network. - Heng Chang; Yu Rong 001; Tingyang Xu; Wenbing Huang 001; Somayeh Sojoudi; Junzhou Huang; Wenwu Zhu 001 (CoRR, 2020)

Dual Message Passing Neural Network for Molecular Property Prediction. - Hehuan Ma; Yatao Bian; Yu Rong 001; Wenbing Huang 001; Tingyang Xu; Weiyang Xie; Geyan Ye; Junzhou Huang (CoRR, 2020)

GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data. - Yu Rong 001; Yatao Bian; Tingyang Xu; Weiyang Xie; Ying Wei 001; Wenbing Huang 001; Junzhou Huang (CoRR, 2020)

Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels? - Tian Bian; Xi Xiao; Tingyang Xu; Yu Rong 001; Wenbing Huang 001; Peilin Zhao; Junzhou Huang (CoRR, 2020)

Tackling Over-Smoothing for General Graph Convolutional Networks. - Wenbing Huang 001; Yu Rong 001; Tingyang Xu; Fuchun Sun 001; Junzhou Huang (CoRR, 2020)

Hybrid-DCA: A double asynchronous approach for stochastic dual coordinate ascent. - Soumitra Pal 001; Tingyang Xu; Tianbao Yang; Sanguthevar Rajasekaran; Jinbo Bi (J. Parallel Distributed Comput., 2020)

Spectral Graph Attention Network with Fast Eigen-approximation. - Heng Chang; Yu Rong 001; Tingyang Xu; Wenbing Huang 001; Somayeh Sojoudi; Junzhou Huang; Wenwu Zhu 001 (CIKM, 2021)

Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding. - Zhehan Liang; Yu Rong 001; Chenxin Li; Yunlong Zhang; Yue Huang 001; Tingyang Xu; Xinghao Ding; Junzhou Huang (CIKM, 2021)

Graph Information Bottleneck for Subgraph Recognition. - Junchi Yu; Tingyang Xu; Yu Rong 001; Yatao Bian; Junzhou Huang; Ran He 001 (ICLR, 2021)

On Self-Distilling Graph Neural Network. - Yuzhao Chen; Yatao Bian; Xi Xiao; Yu Rong 001; Tingyang Xu; Junzhou Huang (IJCAI, 2021)

Not All Low-Pass Filters are Robust in Graph Convolutional Networks. - Heng Chang; Yu Rong 001; Tingyang Xu; Yatao Bian; Shiji Zhou; Xin Wang 019; Junzhou Huang; Wenwu Zhu 001 (NeurIPS, 2021)

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm. - Qifeng Bai; Shuoyan Tan; Tingyang Xu; Huanxiang Liu; Junzhou Huang; Xiaojun Yao (Briefings Bioinform., 2021)

Drug repurposing against breast cancer by integrating drug-exposure expression profiles and drug-drug links based on graph neural network. - Chen Cui; Xiaoyu Ding; Dingyan Wang; Lifan Chen; Fu Xiao; Tingyang Xu; Mingyue Zheng; Xiaomin Luo; Hualiang Jiang; Kaixian Chen (Bioinform., 2021)

Diversified Multiscale Graph Learning with Graph Self-Correction. - Yuzhao Chen; Yatao Bian; Jiying Zhang; Xi Xiao; Tingyang Xu; Yu Rong 001; Junzhou Huang (CoRR, 2021)

Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations. - Yatao Bian; Yu Rong 001; Tingyang Xu; Jiaxiang Wu 001; Andreas Krause 001; Junzhou Huang (CoRR, 2021)

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels. - Xuefeng Du; Tian Bian; Yu Rong 001; Bo Han 003; Tongliang Liu; Tingyang Xu; Wenbing Huang 001; Junzhou Huang (CoRR, 2021)

Local Augmentation for Graph Neural Networks. - Songtao Liu; Hanze Dong; Lanqing Li; Tingyang Xu; Yu Rong 001; Peilin Zhao; Junzhou Huang; Dinghao Wu (CoRR, 2021)

Towards the Explanation of Graph Neural Networks in Digital Pathology with Information Flows. - Junchi Yu; Tingyang Xu; Ran He 001 (CoRR, 2021)

Molecular graph enhanced transformer for retrosynthesis prediction. - Kelong Mao; Xi Xiao; Tingyang Xu; Yu Rong 001; Junzhou Huang; Peilin Zhao (Neurocomputing, 2021)

A Bisection Reinforcement Learning Approach to 3-D Indoor Localization. - Fei Dou; Jin Lu 001; Tingyang Xu; Chun-Hsi Huang; Jinbo Bi (IEEE Internet Things J., 2021)

Equivariant Graph Mechanics Networks with Constraints. - Wenbing Huang 001; Jiaqi Han; Yu Rong 001; Tingyang Xu; Fuchun Sun 001; Junzhou Huang (ICLR, 2022)

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. - Yatao Bian; Yu Rong 001; Tingyang Xu; Jiaxiang Wu 001; Andreas Krause 001; Junzhou Huang (ICLR, 2022)

Local Augmentation for Graph Neural Networks. - Songtao Liu; Rex Ying; Hanze Dong; Lanqing Li; Tingyang Xu; Yu Rong 001; Peilin Zhao; Junzhou Huang; Dinghao Wu (ICML, 2022)

Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction. - Kuangqi Zhou; Kaixin Wang; Jian Tang 005; Jiashi Feng; Bryan Hooi; Peilin Zhao; Tingyang Xu; Xinchao Wang (LoG, 2022)

Equivariant Graph Hierarchy-Based Neural Networks. - Jiaqi Han; Wenbing Huang 001; Tingyang Xu; Yu Rong 001 (NeurIPS, 2022)

Learning Neural Set Functions Under the Optimal Subset Oracle. - Zijing Ou; Tingyang Xu; Qinliang Su; Yingzhen Li; Peilin Zhao; Yatao Bian (NeurIPS, 2022)

Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer. - Erxue Min; Yu Rong 001; Tingyang Xu; Yatao Bian; Da Luo; Kangyi Lin; Junzhou Huang; Sophia Ananiadou; Peilin Zhao (SIGIR, 2022)

Diversified Multiscale Graph Learning with Graph Self-Correction. - Yuzhao Chen; Yatao Bian; Jiying Zhang; Xi Xiao; Tingyang Xu; Yu Rong 001 (TAG-ML, 2022)

Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media. - Erxue Min; Yu Rong 001; Yatao Bian; Tingyang Xu; Peilin Zhao; Junzhou Huang; Sophia Ananiadou (WWW, 2022)

Cross-dependent graph neural networks for molecular property prediction. - Hehuan Ma; Yatao Bian; Yu Rong 001; Wenbing Huang 001; Tingyang Xu; Weiyang Xie; Geyan Ye; Junzhou Huang (Bioinform., 2022)

Multi-instance learning of graph neural networks for aqueous pKa prediction. - Jiacheng Xiong; Zhaojun Li; Guangchao Wang; Zunyun Fu; Feisheng Zhong; Tingyang Xu; Xiaomeng Liu; Ziming Huang; Xiaohong Liu 002; Kaixian Chen; Hualiang Jiang; Mingyue Zheng (Bioinform., 2022)

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. - Yuanfeng Ji; Lu Zhang 060; Jiaxiang Wu 001; Bingzhe Wu; Long-Kai Huang; Tingyang Xu; Yu Rong 001; Lanqing Li; Jie Ren; Ding Xue; Houtim Lai; Shaoyong Xu; et al. (CoRR, 2022)

Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction. - Erxue Min; Yu Rong 001; Tingyang Xu; Yatao Bian; Peilin Zhao; Junzhou Huang; Da Luo; Kangyi Lin; Sophia Ananiadou (CoRR, 2022)

Geometrically Equivariant Graph Neural Networks: A Survey. - Jiaqi Han; Yu Rong 001; Tingyang Xu; Wenbing Huang 001 (CoRR, 2022)

Transformer for Graphs: An Overview from Architecture Perspective. - Erxue Min; Runfa Chen; Yatao Bian; Tingyang Xu; Kangfei Zhao; Wenbing Huang 001; Peilin Zhao; Junzhou Huang; Sophia Ananiadou; Yu Rong 001 (CoRR, 2022)

Equivariant Graph Hierarchy-Based Neural Networks. - Jiaqi Han; Yu Rong 001; Tingyang Xu; Fuchun Sun 001; Wenbing Huang 001 (CoRR, 2022)

Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference. - Zijing Ou; Tingyang Xu; Qinliang Su; Yingzhen Li; Peilin Zhao; Yatao Bian (CoRR, 2022)

Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation. - Runfa Chen; Yu Rong 001; Shangmin Guo; Jiaqi Han; Fuchun Sun 001; Tingyang Xu; Wenbing Huang 001 (CoRR, 2022)

Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs. - Jiying Zhang; Fuyang Li; Xi Xiao; Tingyang Xu; Yu Rong 001; Junzhou Huang; Yatao Bian (CoRR, 2022)

GPN: A Joint Structural Learning Framework for Graph Neural Networks. - Qianggang Ding; Deheng Ye; Tingyang Xu; Peilin Zhao (CoRR, 2022)

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. - Bingzhe Wu; Jintang Li; Junchi Yu; Yatao Bian; Hengtong Zhang; Chaochao Chen 001; Chengbin Hou; Guoji Fu; Liang Chen 001; Tingyang Xu; Yu Rong 001; Xiaolin Zheng; et al. (CoRR, 2022)

Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction. - Kuangqi Zhou; Kaixin Wang; Jiashi Feng; Jian Tang 005; Tingyang Xu; Xinchao Wang (CoRR, 2022)

Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training. - Xueyi Liu; Yu Rong 001; Tingyang Xu; Fuchun Sun 001; Wenbing Huang 001; Junzhou Huang (CoRR, 2022)

Towards Complete-View and High-Level Pose-based Gait Recognition. - Honghu Pan; Yongyong Chen; Tingyang Xu; Yunqi He; Zhenyu He 001 (CoRR, 2022)

Blood-brain barrier penetration prediction enhanced by uncertainty estimation. - Xiaochu Tong; Dingyan Wang; Xiaoyu Ding; Xiaoqin Tan; Qun Ren; Geng Chen; Yu Rong 001; Tingyang Xu; Junzhou Huang; Hualiang Jiang; Mingyue Zheng; Xutong Li (J. Cheminformatics, 2022)

Structure-aware conditional variational auto-encoder for constrained molecule optimization. - Junchi Yu; Tingyang Xu; Yu Rong 001; Junzhou Huang; Ran He 001 (Pattern Recognit., 2022)

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. - Ziqi Gao; Yifan Niu; Jiashun Cheng; Jianheng Tang; Lanqing Li; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009 (AAAI, 2023)

MDM: Molecular Diffusion Model for 3D Molecule Generation. - Lei Huang; Hengtong Zhang; Tingyang Xu; Ka-Chun Wong (AAAI, 2023)

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. - Yuanfeng Ji; Lu Zhang 060; Jiaxiang Wu 001; Bingzhe Wu; Lanqing Li; Long-Kai Huang; Tingyang Xu; Yu Rong 001; Jie Ren; Ding Xue; Houtim Lai; Wei Liu 005; et al. (AAAI, 2023)

Human Mobility Modeling during the COVID-19 Pandemic via Deep Graph Diffusion Infomax. - Yang Liu 165; Yu Rong 001; Zhuoning Guo; Nuo Chen 001; Tingyang Xu; Fugee Tsung; Jia Li 009 (AAAI, 2023)

Decision Support System for Chronic Diseases Based on Drug-Drug Interactions. - Tian Bian; Yuli Jiang; Jia Li 009; Tingyang Xu; Yu Rong 001; Yi Su; Timothy C. Y. Kwok; Helen Meng; Hong Cheng 001 (ICDE, 2023)

Curriculum Graph Poisoning. - Hanwen Liu; Peilin Zhao; Tingyang Xu; Yatao Bian; Junzhou Huang; Yuesheng Zhu; Yadong Mu (WWW, 2023)

Towards Controllable Diffusion Models via Reward-Guided Exploration. - Hengtong Zhang; Tingyang Xu (CoRR, 2023)

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks. - Jiaqi Han; Wenbing Huang 001; Yu Rong 001; Tingyang Xu; Fuchun Sun 001; Junzhou Huang (CoRR, 2023)

Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation. - Yang Liu 165; Jiashun Cheng; Haihong Zhao; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009; Yu Rong 001 (CoRR, 2023)

Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale. - Qichao Wang; Tian Bian; Yian Yin; Tingyang Xu; Hong Cheng 001; Helen M. Meng; Zibin Zheng; Liang Chen 001; Bingzhe Wu (CoRR, 2023)

Computing Graph Edit Distance via Neural Graph Matching. - Chengzhi Piao; Tingyang Xu; Xiangguo Sun; Yu Rong 001; Kangfei Zhao; Hong Cheng 001 (Proc. VLDB Endow., 2023)

Toward Complete-View and High-Level Pose-Based Gait Recognition. - Honghu Pan; Yongyong Chen; Tingyang Xu; Yunqi He; Zhenyu He 001 (IEEE Trans. Inf. Forensics Secur., 2023)

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions. - Xuefeng Du; Tian Bian; Yu Rong 001; Bo Han 003; Tongliang Liu; Tingyang Xu; Wenbing Huang 001; Yixuan Li 001; Junzhou Huang (Trans. Mach. Learn. Res., 2023)

Adversarial Attack Framework on Graph Embedding Models With Limited Knowledge. - Heng Chang; Yu Rong 001; Tingyang Xu; Wenbing Huang 001; Honglei Zhang; Peng Cui 001; Xin Wang 019; Wenwu Zhu 001; Junzhou Huang (IEEE Trans. Knowl. Data Eng., 2023)

Hierarchical Graph Latent Diffusion Model for Conditional Molecule Generation. - Tian Bian; Yifan Niu; Heng Chang; Divin Yan; Junzhou Huang; Yu Rong 001; Tingyang Xu; Jia Li 009; Hong Cheng 001 (CIKM, 2024)

Natural Language-Assisted Multi-modal Medication Recommendation. - Jie Tan; Yu Rong 001; Kangfei Zhao; Tian Bian; Tingyang Xu; Junzhou Huang; Hong Cheng 001; Helen Meng (CIKM, 2024)

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases. - Yang Liu 165; Jiashun Cheng; Haihong Zhao; Tingyang Xu; Peilin Zhao; Fugee Tsung; Jia Li 009; Yu Rong 001 (ICLR, 2024)

Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations. - Ziqiao Meng; Liang Zeng 002; Zixing Song; Tingyang Xu; Peilin Zhao; Irwin King (IJCAI, 2024)

Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. - Haoyu Wang 003; Guozheng Ma; Ziqiao Meng; Zeyu Qin; Li Shen 008; Zhong Zhang; Bingzhe Wu; Liu Liu 014; Yatao Bian; Tingyang Xu; Xueqian Wang 001; Peilin Zhao (CoRR, 2024)

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications. - Jiaqi Han; Jiacheng Cen; Liming Wu; Zongzhao Li; Xiangzhe Kong; Rui Jiao; Ziyang Yu 002; Tingyang Xu; Fandi Wu; Zihe Wang; Hongteng Xu; Zhewei Wei; et al. (CoRR, 2024)

Recognizing Predictive Substructures With Subgraph Information Bottleneck. - Junchi Yu; Tingyang Xu; Yu Rong 001; Yatao Bian; Junzhou Huang; Ran He 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Structure-Aware DropEdge Toward Deep Graph Convolutional Networks. - Jiaqi Han; Wenbing Huang 001; Yu Rong 001; Tingyang Xu; Fuchun Sun 001; Junzhou Huang (IEEE Trans. Neural Networks Learn. Syst., 2024)

RelEdit: Evaluating Conceptual Knowledge Editing in Language Models via Relational Reasoning. - Yifan Niu; Miao Peng; Nuo Chen 001; Yatao Bian; Tingyang Xu; Jia Li 009 (ACL (Findings), 2025)

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization. - Yifan Niu; Ziqi Gao; Tingyang Xu; Yang Liu 165; Yatao Bian; Yu Rong 001; Junzhou Huang; Jia Li 009 (ICLR, 2025)

Large Language-Geometry Model: When LLM meets Equivariance. - Zongzhao Li; Jiacheng Cen; Bing Su 001; Wenbing Huang 001; Tingyang Xu; Yu Rong 001; Deli Zhao (CoRR, 2025)

A Survey of Graph Transformers: Architectures, Theories and Applications. - Chaohao Yuan; Kangfei Zhao; Ercan Engin Kuruoglu; Liang Wang; Tingyang Xu; Wenbing Huang 001; Deli Zhao; Hong Cheng 001; Yu Rong 001 (CoRR, 2025)

STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs. - Zongzhao Li; Zongyang Ma; Mingze Li; Songyou Li; Yu Rong 001; Tingyang Xu; Ziqi Zhang; Deli Zhao; Wen-bing Huang 001 (CoRR, 2025)

Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning. - LASA Team; Weiwen Xu; Hou Pong Chan; Long Li; Mahani Aljunied; Ruifeng Yuan; Jianyu Wang; Chenghao Xiao; Guizhen Chen; Chaoqun Liu; Zhaodonghui Li; Yu Sun; et al. (CoRR, 2025)

ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning. - Yu Sun; Xingyu Qian; Weiwen Xu; Hao Zhang 098; Chenghao Xiao; Long Li; Yu Rong 001; Wenbing Huang 001; Qifeng Bai; Tingyang Xu (CoRR, 2025)

DiffSpectra: Molecular Structure Elucidation from Spectra using Diffusion Models. - Liang Wang 001; Yu Rong 001; Tingyang Xu; Zhenyi Zhong; Zhiyuan Liu; Pengju Wang; Deli Zhao; Qiang Liu 006; Shu Wu; Liang Wang 056 (CoRR, 2025)

VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning. - Ruifeng Yuan; Chenghao Xiao; Sicong Leng; Jianyu Wang; Long Li; Weiwen Xu; Hou Pong Chan; Deli Zhao; Tingyang Xu; Zhongyu Wei; Hao Zhang 048; Yu Rong (CoRR, 2025)

A survey of geometric graph neural networks: data structures, models and applications. - Jiaqi Han; Jiacheng Cen; Liming Wu; Zongzhao Li; Xiangzhe Kong; Rui Jiao; Ziyang Yu 002; Tingyang Xu; Fandi Wu; Zihe Wang; Hongteng Xu; Zhewei Wei; et al. (Frontiers Comput. Sci., 2025)