Taoran Ji

According to our database, Taoran Ji authored at least 23 papers between 2017 and 2024.

Collaborative distances:

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

2024

Citation Forecasting with Multi-Context Attention-Aided Dependency Modeling.

Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu

ACM Trans. Knowl. Discov. Data, July, 2024

Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks.

Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu

ACM Comput. Surv., May, 2024

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction.

Shengkun Wang, Taoran Ji, Linhan Wang, Yanshen Sun, Shang-Ching Liu, Amit Kumar, Chang-Tien Lu

CoRR, 2024

AMA-LSTM: Pioneering Robust and Fair Financial Audio Analysis for Stock Volatility Prediction.

Shengkun Wang, Taoran Ji, Jianfeng He, Mariam Almutairi, Dan Wang, Linhan Wang, Min Zhang, Chang-Tien Lu

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, 2024

Don't Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection.

Min Zhang, Jianfeng He, Taoran Ji, Chang-Tien Lu

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices.

Shengkun Wang, Yangxiao Bai, Taoran Ji, Kaiqun Fu, Linhan Wang, Chang-Tien Lu

Proceedings of the IEEE International Conference on Big Data, 2023

ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction.

Shengkun Wang, Yangxiao Bai, Kaiqun Fu, Linhan Wang, Chang-Tien Lu, Taoran Ji

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2023

2022

On Modeling Dependency Dynamics of Sequential Data: Methods and Applications.

Taoran Ji

PhD thesis, 2022

Granger Causal Inference for Interpretable Traffic Prediction.

Lei Zhang, Kaiqun Fu, Taoran Ji, Chang-Tien Lu

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Blocking Influence at Collective Level with Hard Constraints (Student Abstract).

Zonghan Zhang, Subhodip Biswas, Fanglan Chen, Kaiqun Fu, Taoran Ji, Chang-Tien Lu, Naren Ramakrishnan, Zhiqian Chen

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks.

Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu C. Aggarwal, Chang-Tien Lu

CoRR, 2021

A Hierarchical Attention Graph Convolutional Network for Traffic Incident Impact Forecasting.

Kaiqun Fu, Taoran Ji, Nathan Self, Zhiqian Chen, Chang-Tien Lu

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications.

Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Ethics, Data Science, and Health and Human Services: Embedded Bias in Policy Approaches to Teen Pregnancy Prevention.

Davon Woodard, Huthaifa I. Ashqar, Taoran Ji

CoRR, 2020

Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks.

Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Chang-Tien Lu

CoRR, 2020

2019

Batman or the joker?: the powerful urban computing and its ethics issues.

Kaiqun Fu, Abdulaziz Alhamadani, Taoran Ji, Chang-Tien Lu

ACM SIGSPATIAL Special, 2019

Collect Ethically: Reduce Bias in Twitter Datasets.

Lulwah Alkulaib, Abdulaziz Alhamadani, Taoran Ji, Chang-Tien Lu

Proceedings of the Information Management and Big Data - 6th International Conference, 2019

Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks.

Taoran Ji, Zhiqian Chen, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction.

Kaiqun Fu, Taoran Ji, Liang Zhao, Chang-Tien Lu

Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

Feature driven learning framework for cybersecurity event detection.

Taoran Ji, Xuchao Zhang, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018

Multi-Task Learning for Transit Service Disruption Detection.

Taoran Ji, Kaiqun Fu, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017

Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media.

Rupinder Paul Khandpur, Taoran Ji, Steve T. K. Jan, Gang Wang, Chang-Tien Lu, Naren Ramakrishnan

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Determining Relative Airport Threats from News and Social Media.

Rupinder Paul Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik R. Smith, Christopher Adams, Naren Ramakrishnan

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017