Zhixuan Chu

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 65

Top Topics

Process Automation

Diffusion Models

Causal Inference

Top Venues

Publications

Fangyu Ding, Haiyang Wang, Zhixuan Chu, Tianming Li, Zhaoping Hu, Junchi Yan
GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention. CoRR (2024)
Yanchu Guan, Dong Wang, Zhixuan Chu, Shiyu Wang, Feiyue Ni, Ruihua Song, Chenyi Zhuang
Intelligent Agents with LLM-based Process Automation. KDD (2024)
Zhixuan Chu, Yan Wang, Qing Cui, Longfei Li, Wenqing Chen, Sheng Li, Zhan Qin, Kui Ren
LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation. CoRR (2024)
Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li
A Survey of Trustworthy Representation Learning Across Domains. IEEE Trans. Knowl. Data Eng. 18 (7) (2024)
Zhixuan Chu, Yan Wang, Longfei Li, Zhibo Wang, Zhan Qin, Kui Ren
A Causal Explainable Guardrails for Large Language Models. CoRR (2024)
Guangya Wan, Yuqi Wu, Mengxuan Hu, Zhixuan Chu, Sheng Li
Bridging Causal Discovery and Large Language Models: A Comprehensive Survey of Integrative Approaches and Future Directions. CoRR (2024)
Zhixuan Chu, Lei Zhang, Yichen Sun, Siqiao Xue, Zhibo Wang, Zhan Qin, Kui Ren
Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models. CoRR (2024)
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
Enhancing Event Sequence Modeling with Contrastive Relational Inference. ICASSP (2024)
Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang
Invariant Graph Learning for Causal Effect Estimation. WWW (2024)
Zhibo Wang, Peng Kuang, Zhixuan Chu, Jingyi Wang, Kui Ren
Towards Real World Debiasing: A Fine-grained Analysis On Spurious Correlation. CoRR (2024)
Lei Liu, Xiaoyan Yang, Junchi Lei, Xiaoyang Liu, Yue Shen, Zhiqiang Zhang, Peng Wei, Jinjie Gu, Zhixuan Chu, Zhan Qin, Kui Ren
A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions. CoRR (2024)
Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, Caigao Jiang, Chen Pan, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei
EasyTPP: Towards Open Benchmarking Temporal Point Processes. ICLR (2024)
Zhixuan Chu, Yan Wang, Feng Zhu, Lu Yu, Longfei Li, Jinjie Gu
Professional Agents - Evolving Large Language Models into Autonomous Experts with Human-Level Competencies. CoRR (2024)
Shiyu Wang, Zhixuan Chu, Yinbo Sun, Yu Liu, Yuliang Guo, Yang Chen, Huiyang Jian, Lintao Ma, Xingyu Lu, Jun Zhou
Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting. CoRR (2024)
Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction. AAAI (2024)
Yichen Sun, Zhixuan Chu, Zhan Qin, Kui Ren
Prompt-Consistency Image Generation (PCIG): A Unified Framework Integrating LLMs, Knowledge Graphs, and Controllable Diffusion Models. CoRR (2024)
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
LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs. AAAI (2024)
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
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. ICLR (2024)
Fan Zhou, Siqiao Xue, Danrui Qi, Wenhui Shi, Wang Zhao, Ganglin Wei, Hongyang Zhang, Caigai Jiang, Gangwei Jiang, Zhixuan Chu, Faqiang Chen
DB-GPT-Hub: Towards Open Benchmarking Text-to-SQL Empowered by Large Language Models. CoRR (2024)
Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li
A Survey of Trustworthy Representation Learning Across Domains. ACM Trans. Knowl. Discov. Data 18 (7) (2024)
Zhixuan Chu, Hui Ding, Guang Zeng, Shiyu Wang, Yiming Li
Causal Interventional Prediction System for Robust and Explainable Effect Forecasting. CoRR (2024)
Wenqing Chen, Weicheng Wang, Zhixuan Chu, Kui Ren, Zibin Zheng, Zhichao Lu
Self-Para-Consistency: Improving Reasoning Tasks at Low Cost for Large Language Models. ACL (Findings) (2024)
Zhixuan Chu, Ruopeng Li, Stephen L. Rathbun, Sheng Li
Continual Causal Inference with Incremental Observational Data. CoRR (2023)
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
Leveraging Large Language Models for Pre-trained Recommender Systems. CoRR (2023)
Zhixuan Chu, Ruopeng Li, Stephen L. Rathbun, Sheng Li
Continual Causal Inference with Incremental Observational Data. ICDE (2023)
Dongliang Guo, Zhixuan Chu, Sheng Li
Fair Attribute Completion on Graph with Missing Attributes. CoRR (2023)
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
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. CoRR (2023)
Yunyi Zhou, Zhixuan Chu, Yijia Ruan, Ge Jin, Yuchen Huang, Sheng Li
pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting. CoRR (2023)
Zhixuan Chu, Mechelle Claridy, José Cordero, Sheng Li, Stephen L. Rathbun
Estimating Propensity Scores with Deep Adaptive Variable Selection. SDM (2023)
Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction. CoRR (2023)
Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li
Trustworthy Representation Learning Across Domains. CoRR (2023)
Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang
Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data. CoRR (2023)
Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou, Yijia Wang, Fei Yu, Hong Chen, Wanqing Xu, Xin Lu, Qing Cui, Longfei Li, Jun Zhou, Sheng Li
Data-Centric Financial Large Language Models. CoRR (2023)
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
EasyTPP: Towards Open Benchmarking the Temporal Point Processes. CoRR (2023)
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
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference. ICDM (Workshops) (2023)
Zhixuan Chu, Sheng Li
Continual Treatment Effect Estimation: Challenges and Opportunities. CoRR (2023)
Yunyi Zhou, Zhixuan Chu, Yijia Ruan, Ge Jin, Yuchen Huang, Sheng Li
pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting. IJCAI (2023)
Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang
Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data. CIKM (2023)
Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Y. Zhang, Jun Zhou
Prompt-augmented Temporal Point Process for Streaming Event Sequence. CoRR (2023)
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
Enhancing Recommender Systems with Large Language Model Reasoning Graphs. CoRR (2023)
Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Y. Zhang, Wei Jiang, Siqiao Xue, Jun Zhou
Continual Learning in Predictive Autoscaling. CIKM (2023)
Zhichao Chen, Leilei Ding, Jianmin Huang, Zhixuan Chu, Qingyang Dai, Hao Wang
Unsupervised Anomaly Detection & Diagnosis: A Stein Variational Gradient Descent Approach. CIKM (2023)
Zhixuan Chu, Jianmin Huang, Ruopeng Li, Wei Chu, Sheng Li
Causal Effect Estimation: Recent Advances, Challenges, and Opportunities. CoRR (2023)
Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Zhang, Jun Zhou
Prompt-augmented Temporal Point Process for Streaming Event Sequence. NeurIPS (2023)
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
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference. CoRR (2023)
Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Zhang, Wei Jiang, Siqiao Xue, Jun Zhou
Continual Learning in Predictive Autoscaling. CoRR (2023)
Dongliang Guo, Zhixuan Chu, Sheng Li
Fair Attribute Completion on Graph with Missing Attributes. ICLR (2023)
Zhixuan Chu, Sheng Li
Continual Treatment Effect Estimation: Challenges and Opportunities. AAAI Bridge Program (2023)
Yanchu Guan, Dong Wang, Zhixuan Chu, Shiyu Wang, Feiyue Ni, Ruihua Song, Longfei Li, Jinjie Gu, Chenyi Zhuang
Intelligent Virtual Assistants with LLM-based Process Automation. CoRR (2023)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data. CoRR (2022)
Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin Kang, Sheng Li
Hierarchical Capsule Prediction Network for Marketing Campaigns Effect. CIKM (2022)
Jiayi Liu, Wei Wei, Zhixuan Chu, Xing Gao, Ji Zhang, Tan Yan, Yulin Kang
Incorporating Casual Analysis into Diversified and Logical Response Generation. CoRR (2022)
Jiayi Liu, Wei Wei, Zhixuan Chu, Xing Gao, Ji Zhang, Tan Yan, Yulin Kang
Incorporating Casual Analysis into Diversified and Logical Response Generation. COLING (2022)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data. SDM (2022)
Heng-Shiou Sheu, Zhixuan Chu, Daiqing Qi, Sheng Li
Knowledge-Guided Article Embedding Refinement for Session-Based News Recommendation. IEEE Trans. Neural Networks Learn. Syst. 33 (12) (2022)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials. CHIL (2022)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials. CoRR (2022)
Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin Kang, Sheng Li
Hierarchical Capsule Prediction Network for Marketing Campaigns Effect. CoRR (2022)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. KDD (2021)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. CoRR (2021)
Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang
A Survey on Causal Inference. ACM Trans. Knowl. Discov. Data 15 (5) (2021)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Matching in Selective and Balanced Representation Space for Treatment Effects Estimation. CIKM (2020)
Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao
Causal Inference Meets Machine Learning. KDD (2020)
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Matching in Selective and Balanced Representation Space for Treatment Effects Estimation. CoRR (2020)
Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang
A Survey on Causal Inference. CoRR (2020)