Zhixuan Chu

According to our database, Zhixuan Chu authored at least 36 papers between 2020 and 2024.

Collaborative distances:

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

2024

Bridging Causal Discovery and Large Language Models: A Comprehensive Survey of Integrative Approaches and Future Directions.

Guangya Wan, Yuqi Wu, Mengxuan Hu, Zhixuan Chu, Sheng Li

CoRR, 2024

GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention.

Fangyu Ding, Haiyang Wang, Zhixuan Chu, Tianming Li, Zhaoping Hu, Junchi Yan

CoRR, 2024

Professional Agents - Evolving Large Language Models into Autonomous Experts with Human-Level Competencies.

Zhixuan Chu, Yan Wang, Feng Zhu, Lu Yu, Longfei Li, Jinjie Gu

CoRR, 2024

LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation.

Zhixuan Chu, Yan Wang, Qing Cui, Longfei Li, Wenqing Chen, Sheng Li, Zhan Qin, Kui Ren

CoRR, 2024

LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs.

Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction.

Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Intelligent Virtual Assistants with LLM-based Process Automation.

Yanchu Guan, Dong Wang, Zhixuan Chu, Shiyu Wang, Feiyue Ni, Ruihua Song, Longfei Li, Jinjie Gu, Chenyi Zhuang

CoRR, 2023

Data-Centric Financial Large Language Models.

Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou, Yijia Wang, Fei Yu, Hong Chen, Wanqing Xu, Xin Lu, Qing Cui, Longfei Li, Jun Zhou, Sheng Li

CoRR, 2023

Prompt-augmented Temporal Point Process for Streaming Event Sequence.

Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Y. Zhang, Jun Zhou

CoRR, 2023

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen

CoRR, 2023

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data.

Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang

CoRR, 2023

Trustworthy Representation Learning Across Domains.

Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li

CoRR, 2023

Leveraging Large Language Models for Pre-trained Recommender Systems.

Zhixuan Chu, Hongyan Hao, Xin Ouyang, Simeng Wang, Yan Wang, Yue Shen, Jinjie Gu, Qing Cui, Longfei Li, Siqiao Xue, James Y. Zhang, Sheng Li

CoRR, 2023

Enhancing Recommender Systems with Large Language Model Reasoning Graphs.

Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Y. Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li

CoRR, 2023

Continual Learning in Predictive Autoscaling.

Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Zhang, Wei Jiang, Siqiao Xue, Jun Zhou

CoRR, 2023

EasyTPP: Towards Open Benchmarking the Temporal Point Processes.

Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Fan Zhou, Hongyan Hao, Caigao Jiang, Chen Pan, Yi Xu, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei

CoRR, 2023

Causal Effect Estimation: Recent Advances, Challenges, and Opportunities.

Zhixuan Chu, Jianmin Huang, Ruopeng Li, Wei Chu, Sheng Li

CoRR, 2023

Estimating Propensity Scores with Deep Adaptive Variable Selection.

Zhixuan Chu, Mechelle Claridy, José Cordero, Sheng Li, Stephen L. Rathbun

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

Prompt-augmented Temporal Point Process for Streaming Event Sequence.

Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Zhang, Jun Zhou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting.

Yunyi Zhou, Zhixuan Chu, Yijia Ruan, Ge Jin, Yuchen Huang, Sheng Li

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Fair Attribute Completion on Graph with Missing Attributes.

Dongliang Guo, Zhixuan Chu, Sheng Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference.

Yan Wang, Zhixuan Chu, Tao Zhou, Caigao Jiang, Hongyan Hao, Minjie Zhu, Xindong Cai, Qing Cui, Longfei Li, James Y. Zhang, Siqiao Xue, Jun Zhou

Proceedings of the IEEE International Conference on Data Mining, 2023

Continual Causal Inference with Incremental Observational Data.

Zhixuan Chu, Ruopeng Li, Stephen L. Rathbun, Sheng Li

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Continual Learning in Predictive Autoscaling.

Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Y. Zhang, Wei Jiang, Siqiao Xue, Jun Zhou

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Unsupervised Anomaly Detection & Diagnosis: A Stein Variational Gradient Descent Approach.

Zhichao Chen, Leilei Ding, Jianmin Huang, Zhixuan Chu, Qingyang Dai, Hao Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data.

Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Continual Treatment Effect Estimation: Challenges and Opportunities.

Zhixuan Chu, Sheng Li

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

Knowledge-Guided Article Embedding Refinement for Session-Based News Recommendation.

Heng-Shiou Sheu, Zhixuan Chu, Daiqing Qi, Sheng Li

IEEE Trans. Neural Networks Learn. Syst., 2022

Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data.

Zhixuan Chu, Stephen L. Rathbun, Sheng Li

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Incorporating Casual Analysis into Diversified and Logical Response Generation.

Jiayi Liu, Wei Wei, Zhixuan Chu, Xing Gao, Ji Zhang, Tan Yan, Yulin Kang

Proceedings of the 29th International Conference on Computational Linguistics, 2022

Hierarchical Capsule Prediction Network for Marketing Campaigns Effect.

Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin Kang, Sheng Li

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials.

Zhixuan Chu, Stephen L. Rathbun, Sheng Li

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

A Survey on Causal Inference.

Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang

ACM Trans. Knowl. Discov. Data, 2021

Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data.

Zhixuan Chu, Stephen L. Rathbun, Sheng Li

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Causal Inference Meets Machine Learning.

Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Matching in Selective and Balanced Representation Space for Treatment Effects Estimation.

Zhixuan Chu, Stephen L. Rathbun, Sheng Li

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020