Yan Liu

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 109

Top Venues

Publications

Shihan Dou, Yan Liu, Haoxiang Jia, Enyu Zhou, Limao Xiong, Junjie Shan, Caishuang Huang, Xiao Wang, Xiaoran Fan, Zhiheng Xi, Yuhao Zhou, Tao Ji, Rui Zheng, Qi Zhang, Tao Gui, Xuanjing Huang
StepCoder: Improving Code Generation with Reinforcement Learning from Compiler Feedback. ACL (1) (2024)
Shihan Dou, Haoxiang Jia, Shenxi Wu, Huiyuan Zheng, Weikang Zhou, Muling Wu, Mingxu Chai, Jessica Fan, Caishuang Huang, Yunbo Tao, Yan Liu, Enyu Zhou, Ming Zhang, Yuhao Zhou, Yueming Wu, Rui Zheng, Ming Wen, Rongxiang Weng, Jingang Wang, Xunliang Cai, Tao Gui, Xipeng Qiu, Qi Zhang, Xuanjing Huang
What's Wrong with Your Code Generated by Large Language Models? An Extensive Study. CoRR (2024)
James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister
TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents. ACL (Findings) (2024)
Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Wei Shen, Limao Xiong, Yuhao Zhou, Xiao Wang, Zhiheng Xi, Xiaoran Fan, Shiliang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang
LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin. ACL (1) (2024)
Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. ICLR (2024)
Can Rong, Jingtao Ding, Yan Liu, Yong Li
A Large-scale Benchmark Dataset for Commuting Origin-destination Matrix Generation. CoRR (2024)
James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents. CoRR (2023)
Defu Cao, Zhaowen Wang, Jose Echevarria, Yan Liu
SVGformer: Representation Learning for Continuous Vector Graphics using Transformers. CVPR (2023)
Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. CoRR (2023)
Loc Trinh, Tim Chu, Zijun Cui, Anand Malpani, Cherine Yang, Istabraq Dalieh, Alvin Hui, Oscar Gomez, Yan Liu, Andrew J. Hung
Self-supervised Sim-to-Real Kinematics Reconstruction for Video-Based Assessment of Intraoperative Suturing Skills. MICCAI (9) (2023)
James Enouen, Tianshu Sun, Yan Liu
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments. CoRR (2023)
Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders. AAAI (2023)
Hao Niu, Guillaume Habault, Roberto Legaspi, Chuizheng Meng, Defu Cao, Shinya Wada, Chihiro Ono, Yan Liu
Time-delayed Multivariate Time Series Predictions. SDM (2023)
James Enouen, Yan Liu
Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection. NeurIPS (2022)
Karishma Sharma, Yizhou Zhang, Yan Liu
COVID-19 Vaccine Misinformation Campaigns and Social Media Narratives. ICWSM (2022)
Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui
Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality. CoRR (2022)
Karishma Sharma, Emilio Ferrara, Yan Liu
Characterizing Online Engagement with Disinformation and Conspiracies in the 2020 U.S. Presidential Election. ICWSM (2022)
Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu
Toward Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data. ACM Trans. Spatial Algorithms Syst. 8 (2) (2022)
Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui
Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality. Patterns 3 (12) (2022)
Yizhou Zhang, Defu Cao, Yan Liu
Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media. NeurIPS (2022)
Karishma Sharma, Emilio Ferrara, Yan Liu
Construction of Large-Scale Misinformation Labeled Datasets from Social Media Discourse using Label Refinement. WWW (2022)
Nan Xu, Nitin Kamra, Yan Liu
Treatment Recommendation with Preference-based Reinforcement Learning. ICBK (2021)
Karishma Sharma, Yizhou Zhang, Emilio Ferrara, Yan Liu
Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviours. KDD (2021)
Nitin Kamra, Yan Liu
Gradient-based optimization for multi-resource spatial coverage problems. UAI (2021)
Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla, Chuizheng Meng, Yan Liu
PolSIRD: Modeling Epidemic Spread Under Intervention Policies. J. Heal. Informatics Res. 5 (3) (2021)
Karishma Sharma, Yizhou Zhang, Yan Liu
COVID-19 Vaccines: Characterizing Misinformation Campaigns and Vaccine Hesitancy on Twitter. CoRR (2021)
Chuizheng Meng, Loc Trinh, Nan Xu, Yan Liu
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset. CoRR (2021)
Yizhou Zhang, Karishma Sharma, Yan Liu
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media. NeurIPS (2021)
Karishma Sharma, Xinran He, Sungyong Seo, Yan Liu
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation. ICWSM (2021)
Xiangtian Zheng, Nan Xu, Loc Trinh, Dongqi Wu, Tong Huang, S. Sivaranjani, Yan Liu, Le Xie
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids. CoRR (2021)
Karishma Sharma, Emilio Ferrara, Yan Liu
Characterizing Online Engagement with Disinformation and Conspiracies in the 2020 U.S. Presidential Election. CoRR (2021)
Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning. CoRR (2020)
Karishma Sharma, Pinar Donmez, Enming Luo, Yan Liu, I. Zeki Yalniz
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models. ECCV (27) (2020)
Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu
Multi-agent Trajectory Prediction with Fuzzy Query Attention. CoRR (2020)
Max Guangyu Li, Bo Jiang, Hao Zhu, Zhengping Che, Yan Liu
Generative Attention Networks for Multi-Agent Behavioral Modeling. AAAI (2020)
Karishma Sharma, Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Aastha Dua, Yan Liu
Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations. CoRR (2020)
Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu
Interpretable Deepfake Detection via Dynamic Prototypes. CoRR (2020)
Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. ICLR (2020)
Karishma Sharma, Emilio Ferrara, Yan Liu
Identifying Coordinated Accounts in Disinformation Campaigns. CoRR (2020)
Michael Tsang, Sirisha Rambhatla, Yan Liu
How does this interaction affect me? Interpretable attribution for feature interactions. CoRR (2020)
Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu
Multi-agent Trajectory Prediction with Fuzzy Query Attention. NeurIPS (2020)
Rajesh Gupta, Yan Liu
KDD 2020 Highlights. SIGKDD Explor. 22 (2) (2020)
Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu
Towards Accurate Spatiotemporal COVID-19 Risk Scores using High Resolution Real-World Mobility Data. CoRR (2020)
Karishma Sharma, Xinran He, Sungyong Seo, Yan Liu
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation. CoRR (2020)
Michael Tsang, Sirisha Rambhatla, Yan Liu
How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions. NeurIPS (2020)
Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. CoRR (2020)
Karishma Sharma, Pinar Donmez, Enming Luo, Yan Liu, I. Zeki Yalniz
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models. CoRR (2020)
Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. ICDE (2020)
Zemin Zheng, Mohammad Taha Bahadori, Yan Liu, Jinchi Lv
Scalable Interpretable Multi-Response Regression via SEED. J. Mach. Learn. Res. 20 (2019)
Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu
Combating Fake News: A Survey on Identification and Mitigation Techniques. CoRR (2019)
Hanpeng Liu, Yaguang Li, Michael Tsang, Yan Liu
CoSTCo: A Neural Tensor Completion Model for Sparse Tensors. KDD (2019)
Max Guangyu Li, Bo Jiang, Zhengping Che, Xuefeng Shi, Mengyao Liu, Yiping Meng, Jieping Ye, Yan Liu
DBUS: Human Driving Behavior Understanding System. ICCV Workshops (2019)
Zhengping Che, Max Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye
-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios. CoRR (2019)
Lingyu Zhang, Tianshu Song, Yongxin Tong, Zimu Zhou, Dan Li, Wei Ai, Lulu Zhang, Guobin Wu, Yan Liu, Jieping Ye
Recommendation-based Team Formation for On-demand Taxi-calling Platforms. CIKM (2019)
Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe
Deep Fictitious Play for Games with Continuous Action Spaces. AAMAS (2019)
Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting. AAAI (2019)
Conner Chyung, Michael Tsang, Yan Liu
Extracting Interpretable Concept-Based Decision Trees from CNNs. CoRR (2019)
Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu
Combating Fake News: A Survey on Identification and Mitigation Techniques. ACM Trans. Intell. Syst. Technol. 10 (3) (2019)
Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe
DeepFP for Finding Nash Equilibrium in Continuous Action Spaces. GameSec (2019)
Xu Geng, Xiyu Wu, Lingyu Zhang, Qiang Yang, Yan Liu, Jieping Ye
Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting. CoRR (2019)
Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, Yan Liu
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability. NeurIPS (2018)
Rose Yu, Max Guangyu Li, Yan Liu
Tensor Regression Meets Gaussian Processes. AISTATS (2018)
Michael Tsang, Youbang Sun, Dongxu Ren, Yan Liu
Can I trust you more? Model-Agnostic Hierarchical Explanations. CoRR (2018)
Yan Liu, Zhenhui Li, Wei Ai, Lingyu Zhang
SIGIR 2018 Workshop on Intelligent Transportation Informatics. SIGIR (2018)
Sungyong Seo, Arash Mohegh, George Ban-Weiss, Yan Liu
Automatically Inferring Data Quality for Spatiotemporal Forecasting. ICLR (Poster) (2018)
Michael Tsang, Dehua Cheng, Yan Liu
Detecting Statistical Interactions from Neural Network Weights. ICLR (Poster) (2018)
Sungyong Seo, Hau Chan, P. Jeffrey Brantingham, Jorja Leap, Phebe Vayanos, Milind Tambe, Yan Liu
Partially Generative Neural Networks for Gang Crime Classification with Partial Information. AIES (2018)
Nitin Kamra, Umang Gupta, Fei Fang, Yan Liu, Milind Tambe
Policy Learning for Continuous Space Security Games Using Neural Networks. AAAI (2018)
Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. ICLR (Poster) (2018)
Dehua Cheng, Natali Ruchansky, Yan Liu
Matrix completability analysis via graph k-connectivity. AISTATS (2018)
Feng Qian, ChengYue Gong, Karishma Sharma, Yan Liu
Neural User Response Generator: Fake News Detection with Collective User Intelligence. IJCAI (2018)
Zhengping Che, Sanjay Purushotham, Max Guangyu Li, Bo Jiang, Yan Liu
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series. ICML (2018)
Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, Yan Liu
Multi-task Representation Learning for Travel Time Estimation. KDD (2018)
Palash Goyal, Nitin Kamra, Xinran He, Yan Liu
DynGEM: Deep Embedding Method for Dynamic Graphs. CoRR (2018)
Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu
Benchmarking deep learning models on large healthcare datasets. J. Biomed. Informatics 83 (2018)
Zhengping Che, Yu Cheng, Zhaonan Sun, Yan Liu
Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding. CoRR (2017)
Nitin Kamra, Umang Gupta, Yan Liu
Deep Generative Dual Memory Network for Continual Learning. CoRR (2017)
Yan Liu
Low-Rank tensor regression: Scalability and applications. CAMSAP (2017)
Sungyong Seo, Jing Huang, Hao Yang, Yan Liu
Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction. RecSys (2017)
Sanjay Purushotham, Wilka Carvalho, Tanachat Nilanon, Yan Liu
Variational Recurrent Adversarial Deep Domain Adaptation. ICLR (Poster) (2017)
Rose Yu, Max Guangyu Li, Yan Liu
Tensor Regression Meets Gaussian Processes. CoRR (2017)
Zhengping Che, Yan Liu
Deep Learning Solutions to Computational Phenotyping in Health Care. ICDM Workshops (2017)
Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. ICDM (2017)
Natali Ruchansky, Sungyong Seo, Yan Liu
CSI: A Hybrid Deep Model for Fake News. CoRR (2017)
Zhengping Che, Jennifer L. St. Sauver, Hongfang Liu, Yan Liu
Deep Learning Solutions for Classifying Patients on Opioid Use. AMIA (2017)
Xinran He, Yan Liu
Not Enough Data?: Joint Inferring Multiple Diffusion Networks via Network Generation Priors. WSDM (2017)
Michael Tsang, Dehua Cheng, Yan Liu
Detecting Statistical Interactions from Neural Network Weights. CoRR (2017)
Natali Ruchansky, Sungyong Seo, Yan Liu
CSI: A Hybrid Deep Model for Fake News Detection. CIKM (2017)
Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu
Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. CoRR (2017)
Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. SDM (2017)
Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. CoRR (2017)
Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu
Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets. CoRR (2017)
Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu
Geographic Segmentation via Latent Poisson Factor Model. WSDM (2016)
Huy Pham, Cyrus Shahabi, Yan Liu
Inferring Social Strength from Spatiotemporal Data. ACM Trans. Database Syst. 41 (1) (2016)
Qi Rose Yu, Yan Liu
Learning from Multiway Data: Simple and Efficient Tensor Regression. CoRR (2016)
Rose Yu, Yan Liu
Learning from Multiway Data: Simple and Efficient Tensor Regression. ICML (2016)
Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu
A Survey on Social Media Anomaly Detection. SIGKDD Explor. 18 (1) (2016)
Zhengping Che, Sanjay Purushotham, Robinder G. Khemani, Yan Liu
Interpretable Deep Models for ICU Outcome Prediction. AMIA (2016)
Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David A. Sontag, Yan Liu
Recurrent Neural Networks for Multivariate Time Series with Missing Values. CoRR (2016)
Xinran He, Ke Xu, David Kempe, Yan Liu
Learning Influence Functions from Incomplete Observations. NIPS (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yan Liu