Less Is More: Generating Time Series with LLaMA-Style Autoregression in Simple Factorized Latent Spaces
Siyuan Li, Yifan Sun, Lei Cheng, Lewen Wang, Yang Liu, Weiqing Liu, Jianlong Li, Jiang Bian, Shikai Fang
November 2025
Weiqing Liu
Principal Research Manager
论文与出版物
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Functional Complexity-adaptive Temporal Tensor Decomposition
Panqi Chen, Lei Cheng, Jianlong Li, Weichang Li, Weiqing Liu, Jiang Bian, Shikai Fang
NeurIPS 2025 | October 2025
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R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Yuante Li, Xu Yang, Xiao Yang, Minrui Xu, Xisen Wang, Weiqing Liu, Jiang Bian
NeurIPS 2025 | May 2025
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Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
Panqi Chen, Yifan Sun, Lei Cheng, Yang Yang, Weichang Li, Yang Liu, Weiqing Liu, Jiang Bian, Shikai Fang
NeurIPS 2025 | May 2025
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BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
2024 Neural Information Processing Systems | October 2024
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
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Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
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RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
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MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
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Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
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Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
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Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
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DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
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ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
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Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
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Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
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Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
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Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
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Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
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Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
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A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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Less Is More: Generating Time Series with LLaMA-Style Autoregression in Simple Factorized Latent Spaces
Siyuan Li, Yifan Sun, Lei Cheng, Lewen Wang, Yang Liu, Weiqing Liu, Jianlong Li, Jiang Bian, Shikai Fang
November 2025
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Functional Complexity-adaptive Temporal Tensor Decomposition
Panqi Chen, Lei Cheng, Jianlong Li, Weichang Li, Weiqing Liu, Jiang Bian, Shikai Fang
NeurIPS 2025 | October 2025
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R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Yuante Li, Xu Yang, Xiao Yang, Minrui Xu, Xisen Wang, Weiqing Liu, Jiang Bian
NeurIPS 2025 | May 2025
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Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
Panqi Chen, Yifan Sun, Lei Cheng, Yang Yang, Weichang Li, Yang Liu, Weiqing Liu, Jiang Bian, Shikai Fang
NeurIPS 2025 | May 2025
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BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
2024 Neural Information Processing Systems | October 2024
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
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Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
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RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
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MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
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Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
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DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
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ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
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Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
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Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
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Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
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REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
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Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
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Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
-
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
-
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
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Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Yuante Li, Xu Yang, Xiao Yang, Minrui Xu, Xisen Wang, Weiqing Liu, Jiang Bian
NeurIPS 2025 | May 2025
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
-
Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
-
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
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Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
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Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
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Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
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Less Is More: Generating Time Series with LLaMA-Style Autoregression in Simple Factorized Latent Spaces
Siyuan Li, Yifan Sun, Lei Cheng, Lewen Wang, Yang Liu, Weiqing Liu, Jianlong Li, Jiang Bian, Shikai Fang
November 2025
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Functional Complexity-adaptive Temporal Tensor Decomposition
Panqi Chen, Lei Cheng, Jianlong Li, Weichang Li, Weiqing Liu, Jiang Bian, Shikai Fang
NeurIPS 2025 | October 2025
-
R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Yuante Li, Xu Yang, Xiao Yang, Minrui Xu, Xisen Wang, Weiqing Liu, Jiang Bian
NeurIPS 2025 | May 2025
-
Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
Panqi Chen, Yifan Sun, Lei Cheng, Yang Yang, Weichang Li, Yang Liu, Weiqing Liu, Jiang Bian, Shikai Fang
NeurIPS 2025 | May 2025
-
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
2024 Neural Information Processing Systems | October 2024
-
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
-
Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
-
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
-
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
-
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
-
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
-
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
-
Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
-
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
-
Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
-
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
-
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
-
Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
September 2024
-
Controllable Financial Market Generation with Diffusion Guided Meta Agent
Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
August 2024
-
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
-
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
-
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
-
Qlib: An AI-oriented Quantitative Investment Platform.
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, Tie-Yan Liu
September 2020
-