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Zhixuan Chu
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2020 – today
- 2024
- [j3]Ronghang Zhu
, Dongliang Guo
A Survey of Trustworthy Representation Learning Across Domains. ACM Trans. Knowl. Discov. Data 18(7): 173 (2024) - [c28]Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li:
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction. AAAI 2024: 11642-11650 - [c27]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: 19189-19196 - [c26]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: 14162-14167 - [c25]Zhixuan Chu, Hui Ding, Guang Zeng, Shiyu Wang, Yiming Li:
Causal Interventional Prediction System for Robust and Explainable Effect Forecasting. CIKM 2024: 4431-4438 - [c24]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. CIKM 2024: 4948-4956 - [c23]Yunyi Zhou, Ruohan Gao, Xinping Zheng, Yuchen Huang, Zhixuan Chu:
VMFTransformer: An Angle-Preserving and Auto-Scaling Machine for Multi-Horizon Probabilistic Forecasting. ECAI 2024: 2958-2965 - [c22]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: 6145-6149 - [c21]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 - [c20]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 - [c19]Yanchu Guan
Intelligent Agents with LLM-based Process Automation. KDD 2024: 5018-5027 - [c18]Yongduo Sui
Invariant Graph Learning for Causal Effect Estimation. WWW 2024: 2552-2562 - [i37]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 abs/2401.08217 (2024) - [i36]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 abs/2402.03628 (2024) - [i35]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 abs/2402.07191 (2024) - [i34]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 abs/2402.11068 (2024) - [i33]Zhixuan Chu, Yan Wang, Longfei Li, Zhibo Wang, Zhan Qin, Kui Ren:
A Causal Explainable Guardrails for Large Language Models. CoRR abs/2405.04160 (2024) - [i32]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 abs/2405.04180 (2024) - [i31]Zhibo Wang, Peng Kuang, Zhixuan Chu, Jingyi Wang, Kui Ren:
Towards Real World Debiasing: A Fine-grained Analysis On Spurious Correlation. CoRR abs/2405.15240 (2024) - [i30]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 abs/2406.03712 (2024) - [i29]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 abs/2406.11434 (2024) - [i28]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 abs/2406.16333 (2024) - [i27]Zhixuan Chu, Hui Ding, Guang Zeng, Shiyu Wang, Yiming Li:
Causal Interventional Prediction System for Robust and Explainable Effect Forecasting. CoRR abs/2407.19688 (2024) - [i26]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 abs/2407.19697 (2024) - [i25]Siqiao Xue, Tingting Chen, Fan Zhou, Qingyang Dai, Zhixuan Chu, Hongyuan Mei:
FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering. CoRR abs/2410.04526 (2024) - 2023
- [c17]Zhixuan Chu, Sheng Li:
Continual Treatment Effect Estimation: Challenges and Opportunities. AAAI Bridge Program 2023: 11-17 - [c16]Zhichao Chen
Unsupervised Anomaly Detection & Diagnosis: A Stein Variational Gradient Descent Approach. CIKM 2023: 3783-3787 - [c15]Zhichao Chen
Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data. CIKM 2023: 4523-4529 - [c14]Hongyan Hao
Continual Learning in Predictive Autoscaling. CIKM 2023: 4616-4622 - [c13]Zhixuan Chu, Ruopeng Li, Stephen L. Rathbun, Sheng Li:
Continual Causal Inference with Incremental Observational Data. ICDE 2023: 3430-3439 - [c12]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: 588-592 - [c11]Dongliang Guo, Zhixuan Chu, Sheng Li:
Fair Attribute Completion on Graph with Missing Attributes. ICLR 2023 - [c10]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: 4684-4692 - [c9]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 - [c8]Zhixuan Chu, Mechelle Claridy, José Cordero, Sheng Li, Stephen L. Rathbun:
Estimating Propensity Scores with Deep Adaptive Variable Selection. SDM 2023: 730-738 - [i24]Zhixuan Chu, Sheng Li:
Continual Treatment Effect Estimation: Challenges and Opportunities. CoRR abs/2301.01026 (2023) - [i23]Zhixuan Chu, Jianmin Huang, Ruopeng Li, Wei Chu, Sheng Li:
Causal Effect Estimation: Recent Advances, Challenges, and Opportunities. CoRR abs/2302.00848 (2023) - [i22]Dongliang Guo, Zhixuan Chu, Sheng Li:
Fair Attribute Completion on Graph with Missing Attributes. CoRR abs/2302.12977 (2023) - [i21]Zhixuan Chu, Ruopeng Li, Stephen L. Rathbun, Sheng Li:
Continual Causal Inference with Incremental Observational Data. CoRR abs/2303.01775 (2023) - [i20]Yunyi Zhou, Zhixuan Chu, Yijia Ruan, Ge Jin, Yuchen Huang, Sheng Li:
pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting. CoRR abs/2305.11304 (2023) - [i19]Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Fan Zhou, Hongyan Hao, Caigao Jiang, Chen Pan, Yi Xu, James Y. Zhang, Qingsong Wen
EasyTPP: Towards Open Benchmarking the Temporal Point Processes. CoRR abs/2307.08097 (2023) - [i18]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 abs/2307.15941 (2023) - [i17]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 abs/2308.10835 (2023) - [i16]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 abs/2308.10837 (2023) - [i15]Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, Sheng Li:
Trustworthy Representation Learning Across Domains. CoRR abs/2308.12315 (2023) - [i14]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 abs/2309.02868 (2023) - [i13]Zhichao Chen, Leilei Ding, Zhixuan Chu, Yucheng Qi, Jianmin Huang, Hao Wang
Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data. CoRR abs/2309.13452 (2023) - [i12]Ming Jin, Shiyu Wang
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. CoRR abs/2310.01728 (2023) - [i11]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 abs/2310.04993 (2023) - [i10]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 abs/2310.17784 (2023) - [i9]Yanchu Guan, Dong Wang, Zhixuan Chu, Shiyu Wang
Intelligent Virtual Assistants with LLM-based Process Automation. CoRR abs/2312.06677 (2023) - [i8]Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li:
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction. CoRR abs/2312.16113 (2023) - 2022
- [j2]Heng-Shiou Sheu, Zhixuan Chu
Knowledge-Guided Article Embedding Refinement for Session-Based News Recommendation. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7921-7927 (2022) - [c7]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials. CHIL 2022: 79-91 - [c6]Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin Kang, Sheng Li:
Hierarchical Capsule Prediction Network for Marketing Campaigns Effect. CIKM 2022: 3043-3051 - [c5]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: 378-388 - [c4]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data. SDM 2022: 433-441 - [i7]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data. CoRR abs/2202.10885 (2022) - [i6]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials. CoRR abs/2203.05123 (2022) - [i5]Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin Kang, Sheng Li:
Hierarchical Capsule Prediction Network for Marketing Campaigns Effect. CoRR abs/2208.10113 (2022) - [i4]Jiayi Liu, Wei Wei, Zhixuan Chu, Xing Gao, Ji Zhang, Tan Yan, Yulin Kang:
Incorporating Casual Analysis into Diversified and Logical Response Generation. CoRR abs/2209.09482 (2022) - 2021
- [j1]Liuyi Yao
A Survey on Causal Inference. ACM Trans. Knowl. Discov. Data 15(5): 74:1-74:46 (2021) - [c3]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. KDD 2021: 176-184 - [i3]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. CoRR abs/2106.02881 (2021) - 2020
- [c2]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Matching in Selective and Balanced Representation Space for Treatment Effects Estimation. CIKM 2020: 205-214 - [c1]Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao:
Causal Inference Meets Machine Learning. KDD 2020: 3527-3528 - [i2]Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang:
A Survey on Causal Inference. CoRR abs/2002.02770 (2020) - [i1]Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Matching in Selective and Balanced Representation Space for Treatment Effects Estimation. CoRR abs/2009.06828 (2020)
Coauthor Index
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