NesTPP: Modeling Thread Dynamics in Online Discussion Forums. - Chen Ling 003; Guangmo Tong; Mozi Chen (HT, 2020)

Time-constrained Adaptive Influence Maximization. - Guangmo Tong; Ruiqi Wang; Chen Ling 003; Zheng Dong 002; Xiang Li 016 (CoRR, 2020)

SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting. - Chen Ling 003; Ruiqi Wang; Guangmo Tong (CoRR, 2020)

Deep Generation of Heterogeneous Networks. - Chen Ling 003; Carl Yang 001; Liang Zhao 002 (ICDM, 2021)

On Forecasting Dynamics In Online Discussion Forums. - Chen Ling 003; Di Cui; Guangmo Tong; Jianming Zhu (ICME, 2021)

TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints. - Liming Zhang; Liang Zhao 002; Shan Qin; Dieter Pfoser; Chen Ling 003 (WWW, 2021)

DeepGAR: Deep Graph Learning for Analogical Reasoning. - Chen Ling 003; Tanmoy Chowdhury; Junji Jiang; Junxiang Wang; Xuchao Zhang; Haifeng Chen; Liang Zhao 002 (ICDM, 2022)

Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems. - Chen Ling 003; Junji Jiang; Junxiang Wang; Liang Zhao 002 (KDD, 2022)

STGEN: Deep Continuous-Time Spatiotemporal Graph Generation. - Chen Ling 003; Hengning Cao; Liang Zhao 002 (ECML/PKDD (3), 2022)

Open-ended Commonsense Reasoning with Unrestricted Answer Candidates. - Chen Ling 003; Xuchao Zhang; Xujiang Zhao; Yanchi Liu; Wei Cheng 002; Mika Oishi; Takao Osaki; Katsushi Matsuda; Haifeng Chen; Liang Zhao 002 (EMNLP (Findings), 2023)

Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks. - Guangji Bai; Chen Ling 003; Liang Zhao 002 (ICLR, 2023)

Deep Graph Representation Learning and Optimization for Influence Maximization. - Chen Ling 003; Junji Jiang; Junxiang Wang; My T. Thai; Renhao Xue; James Song; Meikang Qiu; Liang Zhao 002 (ICML, 2023)

Saliency-Augmented Memory Completion for Continual Learning. - Guangji Bai; Chen Ling 003; Yuyang Gao; Liang Zhao 002 (SDM, 2023)

Knowledge-enhanced Neural Machine Reasoning: A Review. - Tanmoy Chowdhury; Chen Ling 003; Xuchao Zhang; Xujiang Zhao; Guangji Bai; Jian Pei 001; Haifeng Chen; Liang Zhao 002 (CoRR, 2023)

Deep Graph Representation Learning and Optimization for Influence Maximization. - Chen Ling 003; Junji Jiang; Junxiang Wang; My T. Thai; Lukas Xue; James Song; Meikang Qiu; Liang Zhao 002 (CoRR, 2023)

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models. - Chen Ling 003; Xujiang Zhao; Jiaying Lu 001; Chengyuan Deng; Can Zheng; Junxiang Wang; Tanmoy Chowdhury; Yun Li 005; Hejie Cui; Xuchao Zhang; Tianjiao Zhao; Amit Panalkar; et al. (CoRR, 2023)

A Survey on Knowledge Graphs for Healthcare: Resources, Applications, and Promises. - Hejie Cui; Jiaying Lu 001; Shiyu Wang 002; Ran Xu 002; Wenjing Ma; Shaojun Yu; Yue Yu 001; Xuan Kan; Chen Ling 003; Joyce C. Ho; Fei Wang; Carl Yang 001 (CoRR, 2023)

Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty. - Chen Ling 003; Xujiang Zhao; Xuchao Zhang; Yanchi Liu; Wei Cheng 002; Haoyu Wang; Zhengzhang Chen; Takao Osaki; Katsushi Matsuda; Haifeng Chen; Liang Zhao 002 (CoRR, 2023)

Open-ended Commonsense Reasoning with Unrestricted Answer Scope. - Chen Ling 003; Xuchao Zhang; Xujiang Zhao; Yanchi Liu; Wei Cheng 002; Mika Oishi; Takao Osaki; Katsushi Matsuda; Haifeng Chen; Liang Zhao 002 (CoRR, 2023)

Motif-guided heterogeneous graph deep generation. - Chen Ling 003; Carl Yang 001; Liang Zhao 002 (Knowl. Inf. Syst., 2023)

ELAD: Explanation-Guided Large Language Models Active Distillation. - Yifei Zhang 006; Bo Pan; Chen Ling 003; Yuntong Hu; Liang Zhao 002 (ACL (Findings), 2024)

MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization. - Nguyen Hoang Khoi Do; Tanmoy Chowdhury; Chen Ling 003; Liang Zhao 002; My T. Thai (AISTATS, 2024)

Zero-Shot Link Prediction in Knowledge Graphs with Large Language Models. - Mingchen Li; Chen Ling 003; Rui Zhang 028; Liang Zhao 002 (ICDM, 2024)

Source Localization for Cross Network Information Diffusion. - Chen Ling 003; Tanmoy Chowdhury; Jie Ji; Sirui Li; Andreas Züfle; Liang Zhao 002 (KDD, 2024)

Uncertainty Quantification for In-Context Learning of Large Language Models. - Chen Ling 003; Xujiang Zhao; Xuchao Zhang; Wei Cheng 002; Yanchi Liu; Yiyou Sun; Mika Oishi; Takao Osaki; Katsushi Matsuda; Jie Ji; Guangji Bai; Liang Zhao 002; et al. (NAACL-HLT, 2024)

SparseLLM: Towards Global Pruning of Pre-trained Language Models. - Guangji Bai; Yijiang Li; Chen Ling 003; Kibaek Kim; Liang Zhao 002 (NeurIPS, 2024)

TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs. - Zhuofeng Li; Zixing Gou; Xiangnan Zhang; Zhongyuan Liu; Sirui Li; Yuntong Hu; Chen Ling 003; Zheng Zhang 047; Liang Zhao 002 (NeurIPS, 2024)

Helper Recommendation with seniority control in Online Health Community. - Junruo Gao; Chen Ling 003; Carl Yang 001; Liang Zhao 002 (SDM, 2024)

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models. - Guangji Bai; Zheng Chai; Chen Ling 003; Shiyu Wang 002; Jiaying Lu 001; Nan Zhang; Tingwei Shi; Ziyang Yu; Mengdan Zhu; Yifei Zhang 006; Carl Yang 001; Yue Cheng 001; et al. (CoRR, 2024)

Gene-associated Disease Discovery Powered by Large Language Models. - Jiayu Chang; Shiyu Wang 002; Chen Ling 003; Zhaohui Qin; Liang Zhao 002 (CoRR, 2024)

Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models. - Chen Ling 003; Xujiang Zhao; Wei Cheng 002; Yanchi Liu; Yiyou Sun; Xuchao Zhang; Mika Oishi; Takao Osaki; Katsushi Matsuda; Jie Ji; Guangji Bai; Liang Zhao 002; et al. (CoRR, 2024)

A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models. - Mingchen Li; Chen Ling 003; Rui Zhang 028; Liang Zhao 002 (CoRR, 2024)

MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization. - Nguyen Do; Tanmoy Chowdhury; Chen Ling 003; Liang Zhao 002; My T. Thai (CoRR, 2024)

Gradient-Free Adaptive Global Pruning for Pre-trained Language Models. - Guangji Bai; Yijiang Li; Chen Ling 003; Kibaek Kim; Liang Zhao 002 (CoRR, 2024)

Link Prediction on Textual Edge Graphs. - Chen Ling 003; Zhuofeng Li; Yuntong Hu; Zheng Zhang 047; Zhongyuan Liu; Shuang Zheng; Liang Zhao 002 (CoRR, 2024)

TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations. - Zheng Zhang 047; Yuntong Hu; Bo Pan; Chen Ling 003; Liang Zhao 002 (CoRR, 2024)

HiReview: Hierarchical Taxonomy-Driven Automatic Literature Review Generation. - Yuntong Hu; Zhuofeng Li; Zheng Zhang 047; Chen Ling 003; Raasikh Kanjiani; Boxin Zhao; Liang Zhao 002 (CoRR, 2024)

Quantifying uncertainty in graph neural network explanations. - Junji Jiang; Chen Ling 003; Hongyi Li; Guangji Bai; Xujiang Zhao; Liang Zhao 002 (Frontiers Big Data, 2024)

Deep graph representation learning influence maximization with accelerated inference. - Tanmoy Chowdhury; Chen Ling 003; Junji Jiang; Junxiang Wang; My T. Thai; Liang Zhao 002 (Neural Networks, 2024)

GRAG: Graph Retrieval-Augmented Generation. - Yuntong Hu; Zhihan Lei; Zheng Zhang 047; Bo Pan; Chen Ling 003; Liang Zhao 002 (NAACL (Findings), 2025)

A review on knowledge graphs for healthcare: Resources, applications, and promises. - Hejie Cui; Jiaying Lu 001; Ran Xu 002; Shiyu Wang 002; Wenjing Ma; Yue Yu 001; Shaojun Yu; Xuan Kan; Chen Ling 003; Liang Zhao 002; Zhaohui S. Qin; Joyce C. Ho; et al. (J. Biomed. Informatics, 2025)