Chen Ling

According to our database, Chen Ling authored at least 37 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Deep graph representation learning influence maximization with accelerated inference.

Tanmoy Chowdhury, Chen Ling, Junji Jiang, Junxiang Wang, My T. Thai, Liang Zhao

Neural Networks, 2024

Quantifying uncertainty in graph neural network explanations.

Junji Jiang, Chen Ling, Hongyi Li, Guangji Bai, Xujiang Zhao, Liang Zhao

Frontiers Big Data, 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, Zheng Zhang, Liang Zhao

CoRR, 2024

TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations.

Zheng Zhang, Yuntong Hu, Bo Pan, Chen Ling, Liang Zhao

CoRR, 2024

Link Prediction on Textual Edge Graphs.

Chen Ling, Zhuofeng Li, Yuntong Hu, Zheng Zhang, Zhongyuan Liu, Shuang Zheng, Liang Zhao

CoRR, 2024

GRAG: Graph Retrieval-Augmented Generation.

Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, Liang Zhao

CoRR, 2024

Gradient-Free Adaptive Global Pruning for Pre-trained Language Models.

Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, Liang Zhao

CoRR, 2024

MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization.

Nguyen Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai

CoRR, 2024

A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models.

Mingchen Li, Chen Ling, Rui Zhang, Liang Zhao

CoRR, 2024

Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models.

Chen Ling, Xujiang Zhao, Wei Cheng, Yanchi Liu, Yiyou Sun, Xuchao Zhang, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen

CoRR, 2024

Gene-associated Disease Discovery Powered by Large Language Models.

Jiayu Chang, Shiyu Wang, Chen Ling, Zhaohui Qin, Liang Zhao

CoRR, 2024

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models.

Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao

CoRR, 2024

Helper Recommendation with seniority control in Online Health Community.

Junruo Gao, Chen Ling, Carl Yang, Liang Zhao

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Uncertainty Quantification for In-Context Learning of Large Language Models.

Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Source Localization for Cross Network Information Diffusion.

Chen Ling, Tanmoy Chowdhury, Jie Ji, Sirui Li, Andreas Züfle, Liang Zhao

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization.

Nguyen Hoang Khoi Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

ELAD: Explanation-Guided Large Language Models Active Distillation.

Yifei Zhang, Bo Pan, Chen Ling, Yuntong Hu, Liang Zhao

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Motif-guided heterogeneous graph deep generation.

Chen Ling, Carl Yang, Liang Zhao

Knowl. Inf. Syst., July, 2023

Open-ended Commonsense Reasoning with Unrestricted Answer Scope.

Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

CoRR, 2023

Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty.

Chen Ling, Xujiang Zhao, Xuchao Zhang, Yanchi Liu, Wei Cheng, Haoyu Wang, Zhengzhang Chen, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

CoRR, 2023

A Survey on Knowledge Graphs for Healthcare: Resources, Applications, and Promises.

Hejie Cui, Jiaying Lu, Shiyu Wang, Ran Xu, Wenjing Ma, Shaojun Yu, Yue Yu, Xuan Kan, Chen Ling, Joyce C. Ho, Fei Wang, Carl Yang

CoRR, 2023

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models.

Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Carl Yang, Liang Zhao

CoRR, 2023

Deep Graph Representation Learning and Optimization for Influence Maximization.

Chen Ling, Junji Jiang, Junxiang Wang, My T. Thai, Lukas Xue, James Song, Meikang Qiu, Liang Zhao

CoRR, 2023

Knowledge-enhanced Neural Machine Reasoning: A Review.

Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao

CoRR, 2023

Saliency-Augmented Memory Completion for Continual Learning.

Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Deep Graph Representation Learning and Optimization for Influence Maximization.

Chen Ling, Junji Jiang, Junxiang Wang, My T. Thai, Renhao Xue, James Song, Meikang Qiu, Liang Zhao

Proceedings of the International Conference on Machine Learning, 2023

Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks.

Guangji Bai, Chen Ling, Liang Zhao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Open-ended Commonsense Reasoning with Unrestricted Answer Candidates.

Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

STGEN: Deep Continuous-Time Spatiotemporal Graph Generation.

Chen Ling, Hengning Cao, Liang Zhao

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems.

Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

DeepGAR: Deep Graph Learning for Analogical Reasoning.

Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints.

Liming Zhang, Liang Zhao, Shan Qin, Dieter Pfoser, Chen Ling

Proceedings of the WWW '21: The Web Conference 2021, 2021

On Forecasting Dynamics In Online Discussion Forums.

Chen Ling, Di Cui, Guangmo Tong, Jianming Zhu

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Deep Generation of Heterogeneous Networks.

Chen Ling, Carl Yang, Liang Zhao

Proceedings of the IEEE International Conference on Data Mining, 2021

2020

SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting.

Chen Ling, Ruiqi Wang, Guangmo Tong

CoRR, 2020

Time-constrained Adaptive Influence Maximization.

Guangmo Tong, Ruiqi Wang, Chen Ling, Zheng Dong, Xiang Li

CoRR, 2020

NesTPP: Modeling Thread Dynamics in Online Discussion Forums.

Chen Ling, Guangmo Tong, Mozi Chen

Proceedings of the HT '20: 31st ACM Conference on Hypertext and Social Media, 2020